Jarno Mielikainen

• D.Sc. (Tech.)
• University of Wisconsin–Madison

This chapter examines the optimization of numerical weather prediction through optimizations that include reducing the memory bound nature of the code. Code restructuring for better vectorization is also shown to be essential for such a legacy code. The code that is optimized is the weather research and forecasting model, an open source numerical w...

A high-order clustered differential pulse code modulation method with removal of local spectral outliers (C-DPCM-RLSO) is proposed for the lossless compression of hyperspectral images. By adaptively removing the local spectral outliers, the C-DPCM-RLSO method improves the prediction accuracy of the high-order regression predictor and reduces the re...

Due to severe weather events, there is a growing need for more accurate weather predictions. Climate change has increased both frequency and severity of such events. Optimizing weather model source code would result in reduced run times or more accurate weather predictions. One such weather model is the weather research and forecasting (WRF) model,...

Next-generation mesoscale numerical weather prediction system, the Weather Research and Forecasting (WRF) model, is a designed for dual use for forecasting and research. WRF offers multiple physics options that can be combined in any way. One of the physics options is radiance computation. The major source for energy for the earth's climate is sola...

The Thompson cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Thompson scheme incorporates a large numb...

The planetary boundary layer (PBL) is the lowest part of the atmosphere and where its character is directly affected by its contact with the underlying planetary surface. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transport in the whole atmospheric column. It determines the flux profiles within the well-mixed boundary lay...

In order to make use of the ever-improving microprocessor performance, the applications must be modified to take advantage of the parallelism of today’s microprocessors. One such application that needs to be modernized is the weather research and forecasting (WRF) model, which is designed for numerical weather prediction and atmospheric research. T...

Radiative transfer of electromagnetic radiation through a planetary atmosphere is computed using an atmospheric radiative transfer model (RTM). One RTM is the rapid RTM (RRTM), which calculates both longwave and shortwave atmospheric radiative fluxes and heating rates. Broadband radiative transfer code for general circulation model (GCM) applicatio...

The most widely used community weather forecast and research model in the world is the Weather Research and Forecast (WRF) model. Two distinct varieties of WRF exist. The one we are interested is the Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-...

Intel Many Integrated Core (MIC) ushers in a new era of supercomputing speed, performance, and compatibility. It allows the developers to run code at trillions of calculations per second using the familiar programming model. In this paper, we present our results of optimizing the updated Goddard shortwave radiation Weather Research and Forecasting...

Satellite remote-sensing observations and ground-based radar can detect the weather conditions from a distance and are widely used to monitor the weather all around the globe. The assimilated satellite/radar data are passed through the weather models for weather forecasting. The five-layer thermal diffusion scheme is one of the weather models, hand...

An atmospheric radiative transfer model calculates radiative transfer of electromagnetic radiation through earth’s atmosphere. The community radiative transfer model (CRTM) is a fast radiative transfer model for calculating the satellite infrared (IR) and microwave (MW) radiances of a given state of the Earth’s atmosphere and its surface. The CRTM...

The Weather Research and Forecasting (WRF) model is a numerical weather prediction system designed to serve both atmospheric research and operational forecasting needs. The WRF development is a done in collaboration around the globe. Furthermore, the WRF is used by academic atmospheric scientists, weather forecasters at the operational centers and...

The planetary boundary layer (PBL) is the lowest part of the atmosphere and where its character is directly affected by its contact with the underlying planetary surface. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transport in the whole atmospheric column. It determines the flux profiles within the well-mixed boundary lay...

The Weather Research and Forecast (WRF) model is the most widely used community weather forecast and research model in the world. There are two distinct varieties of WRF. The Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed fo...

Purdue-Lin scheme is a relatively sophisticated microphysics scheme in the Weather Research and Forecasting (WRF) model. The scheme includes six classes of hydro meteors: water vapor, cloud water, raid, cloud ice, snow and graupel. The scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid poin...

The Goddard cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The WRF is a widely used weather prediction system in the world. It development is a done in collaborative around the globe. The Goddard microphysics scheme is very suitable for massively parallel computation as th...

Atmospheric radiative transfer models calculate radiative transfer of electromagnetic radiation through a planetary atmosphere. One of such models is the rapid radiative transfer model (RRTM), which evaluates longwave and shortwave atmospheric radiative fluxes and heating rates. The RRTM for general circulation models (GCMs), RRTMG, is an accelerat...

The Thompson cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Thompson scheme incorporates a large numb...

The Weather Research and Forecasting (WRF) model is designed for numerical weather prediction and atmospheric research. The WRF software infrastructure consists of several components such as dynamic solvers and physics schemes. Numerical models are used to resolve the large-scale flow. However, subgrid-scale parameterizations are for an estimation...

The Weather Research and Forecasting model (WRF) double-moment 6-class microphysics scheme (WDM6) implements a double-moment bulk microphysical parameterization of clouds and precipitation and is applicable in mesoscale and general circulation models. WDM6 extends the WRF single-moment 6-class microphysics scheme (WSM6) by incorporating the number...

An Atmospheric radiative transfer model calculates radiative transfer of electromagnetic radiation through a planetary atmosphere. Both shortwave radiance and longwave radiance parameterizations in an atmospheric model calculate radiation fluxes and heating rates in the earth-atmospheric system. One radiative transfer model is the rapid radiative t...

In recent years, graphics processing units (GPUs) have emerged as a low-cost, low-power and a very high performance alternative to conventional central processing units (CPUs). The latest GPUs offer a speedup of two-to-three orders of magnitude over CPU for various science and engineering applications. The Weather Research and Forecasting (WRF) mod...

This letter explores the use of adaptive prediction length in clustered differential pulse code modulation (C-DPCM) lossless compression method for hyperspectral images. In the C-DPCM method, linear prediction is performed using coefficients optimized for each spectral cluster separately. The difference between the predicted and original values is...

An Atmospheric radiative transfer model calculates radiative transfer of electromagnetic radiation through earth's atmosphere. The Community Radiative Transfer Model (CRTM) is a fast model for simulating the infrared (IR) and microwave (MW) radiances of a given state of the Earth's atmosphere and its surface. The CRTM radiances have been used for s...

The Weather Research and Forecasting (WRF) is a system of numerical weather prediction and atmospheric simulation with dual purposes for forecasting and research. The WRF software infrastructure consists of several components such as dynamic solvers and physical simulation modules. WRF includes several Land-Surface Models (LSMs). The LSMs use atmos...

The Eta Ferrier cloud microphysics scheme is a sophisticated cloud microphysics module in the Weather Research and Forecasting (WRF) model. In this paper, we present the approach and the results of accelerating the Eta Ferrier microphysics scheme on NVIDIA Graphics Processing Units (GPUs). We discuss how our GPU implementation takes advantage of th...

The Weather Research and Forecasting (WRF) model is an atmospheric simulation system which is designed for both operational and research use. WRF is currently in operational use at the National Oceanic and Atmospheric Administration (NOAA)'s national weather service as well as at the air force weather agency and meteorological services worldwide. G...

Next-generation mesoscale numerical weather prediction system, the Weather Research and Forecasting (WRF) model, is a designed for dual use for forecasting and research. WRF offers multiple physics options that can be combined in any way. One of the physics options is radiance computation. The major source for energy for the earth's climate is sola...

The Weather Research and Forecasting (WRF) model is a next-generation mesoscale numerical weather prediction system. It is designed to serve the needs of both operational forecasting and atmospheric research for a broad spectrum of applications across scales ranging from meters to thousands of kilometers. Microphysics plays an important role in wea...

This chapter gives an overview of the lookup table (LUT) based lossless compression methods for hyperspectral images. The LUT method searches the previous band for a pixel of equal value to the pixel co-located to the one to be coded. The pixel in the same position as the obtained pixel in the current band is used as the predictor. Lookup tables ar...

The Weather Research and Forecasting (WRF) model is a next-generation mesoscale numerical weather prediction system. Microphysics plays an important role in weather and climate prediction. Several bulk water microphysics schemes are available within the WRF, with different numbers of simulated hydrometeor classes and methods for estimating their si...

In this paper, we develop a novel Graphics Processing Unit (GPU)-based high-performance Radiative Transfer Model (RTM) for the Infrared Atmospheric Sounding Interferometer (IASI) launched in 2006 onboard the first European meteorological polar-orbiting satellites, METOP-A. The proposed GPU RTM processes more than one profile at a time in order to g...

The Weather Research and Forecast (WRF) model is the most widely used community weather forecast and research model in the world. There are several single moment ice microphysics models in WRF. A mixed phase for WRF Single Moment (WSM) represents the condensation, precipitation, and thermodynamic effects of latent heat release. In this paper, we wi...

Several bulk water microphysics schemes are available within the Weather Research and Forecasting (WRF) model, with different numbers of simulated hydrometeor classes and methods for estimating their size fall speeds, distributions and densities. Stony-Brook University (SBU-YLIN) microphysics scheme is a 5-class scheme with riming intensity predict...

We have developep a Graphics Processing Unit (GPU)-based high-performance radiative transfer model (RTM) for the Infrared Atmospheric Sounding Interferometer (IASI). We propose two different types of GPU RTMs. The first one, processes one profile at a time. The second proposed GPU RTM processes more than one profile at a time in order to gain a sig...

With the rapid advances of the internet and other multimedia technologies, the digital document market has been growing steadily. Since most digital images use halftone technologies, quality degradation occurs when one tries to scan and reprint them. Therefore, it is necessary to extract the halftone areas to produce high quality printing. In this...

Recently, high quality video services have become widely available. To transmit or store these HD video programs, compression is required and various lossy compression schemes have been developed. On the other hand, there are some applications which require lossless compression. However, most conventional lossless coding methods have high complexit...

In this paper, we will presents our results in accelerating Radiative Transfer for TOVS (RTTOV) Radiative Transfer Model (RTM) scheme on many-core NVIDIA graphics processing units (GPUs). GPUs have evolved into a highly parallel, multi-threaded, many-core processors with tremendous computational speed and a high memory bandwidth. We will discuss ho...

Satellite-observed radiance is a nonlinear functional of surface properties and atmospheric temperature and absorbing gas profiles as described by the radiative transfer equation (RTE). In the era of hyperspectral sounders with thousands of high-resolution channels, the computation of the radiative transfer model becomes more time-consuming. The ra...

The radiative transfer for television operational vertical sounder (RTTOV) is a widely-used radiative transfer model (RTM) for calculation of radiances for satellite infrared and microwave sensors, including the 8461-channel infrared atmospheric sounding interferometer (IASI) and the 15-band Advanced Microwave Sounding Unit-A (AMSU-A). In the era o...

The amount of data generated by ultraspectral sounders is so large that considerable savings in data storage and transmission bandwidth can be achieved using data compression. Due to this large amount of data, the data compression time is of utmost importance. Increasing the programmability of the commodity Graphics Processing Units (GPUs) offer po...

We develop a Graphics Processing Unit (GPU)-based high-performance RTTOV-7 forward model. The RTTOV forward model performs the fast computation of the radiances, brightness temperatures, overcast radiances, surface to space transmittances, surface emissivities and pressure level to space transmittances for a given profile vector. A special optimize...

This paper extends clustered differential pulse code modulation (C-DPCM) lossless compression method for hyperspectral images. In C-DPCM method the spectra of a hyperspectral image is clustered, and an optimized predictor is calculated for each cluster. Prediction is performed using a linear predictor. After prediction, the difference between the p...

This letter presents a lossless compression method for ultraspectral sounder data. The method utilizes spectral linear prediction that exploits statistical similarities between different granules. The linear prediction with optimal granule ordering (LP-OGO) method computes linear prediction coefficients using a different granule. That approach requ...

The amount of data generated by hyper- and ultraspectral imagers is so large that considerable savings in data storage and transmission bandwidth can be achieved using data compression. Due to the large amount of data, the data compression time is of importance. Increasing programmability of commodity Graphics Processing Units (GPUs) allows their u...

In this paper, a designing process and implementation details of an intelligent Bluetooth-enabled robot car are described. The robot car is wirelessly remote controlled via Bluetooth. In addition, a comparative analysis of the different kinds of sensors, which are useful in robot cars, is provided. Moreover, a review of the wireless robot car remot...

A line printer daemon (LPR) protocol and a raw transmission control protocol/Internet protocol (raw TCP/IP) are widely used as data communication protocols in office multifunctional devices. Surprisingly, the efficiency of these protocols has not been analyzed. Therefore, a comparative efficiency analysis of the LPR and raw TCP/IP printing protocol...

In this paper, a designing process and implementation details of an intelligent ZigBee and wireless local area network (WLAN) enabled robot car are described. ZigBee was used for the delivery of the robot car controlling commands, while WLAN was used for in-car image transmission to the controlling computer. In addition, intelligent solutions curre...

In this paper, a designing process and implementation details of an intelligent X-10-enabled home are described. Our intelligent home is suitable for both the ordinary people and for the so-called computer professionals or home intelligence enthusiasts. In addition, a comparison with other related research is provided. Moreover, intelligent solutio...

We propose a novel method for lossless compression of ultraspectral sounder data. The method utilizes spectral linear prediction and the optimal ordering of the granules. The prediction coefficients for a granule are computed using prediction coefficients that are optimized using a different granule. The optimal ordering problem is solved using Edm...

We propose an enhancement to the algorithm for lossless compression of hyperspectral images using lookup tables (LUTs). The original LUT method searched the previous band for a pixel of equal value to the pixel colocalized with the one to be predicted. The pixel in the same position as the obtained pixel in the current band is used as a predictor....

In paper industry, the measurement of paper surface topography is important for paper quality control. Noncontact and fast photometric stereo overcomes the disadvantages of the traditional surface topography measurement by the profilometer. In this paper, we present an improvement to three-light photometric stereo for paper surface topography recon...

This paper proposes an interband version of the linear prediction approach for hyperspectral images. Linear prediction represents one of the best performing and most practical and general purpose lossless image compression techniques known today. The interband linear prediction method consists of two stages: predictive decorrelation producing resid...

This letter proposes a modification to the least-significant-bit (LSB) matching, a steganographic method for embedding message bits into a still image. In the LSB matching, the choice of whether to add or subtract one from the cover image pixel is random. The new method uses the choice to set a binary function of two cover pixels to the desired val...

In this letter, we propose a new algorithm for lossless compression of hyperspectral images. The proposed method searches the previous band for a pixel of equal value to the pixel co-located to the one to be coded. The pixel in the same position as the obtained pixel in the current band is used as the predictor. Lookup tables are used to speed up t...

This article presents a method to remove watermarks from watermarked spectral images. The watermarks were added through the Principal Component Analysis (PCA). The removal is also performed using the PCA transform. Experimental results indicate that the removal of the watermark can be performed successfully.

In this paper we present a method for optical paper surface roughness measurement, which overcomes the disadvantages of the traditional methods. Airflow-based roughness measurement methods and profilometer require expensive special equipment, essential laboratory conditions, are contact-based and slow and unsuitable for on-line control purposes met...

In this paper we present an efficient method for reducing the required compression time. The method is based on a reduction of the number of pixels that are used in prediction coefficient estimation for linear predictor. The estimation is performed on a subset of the all image data points. While the compression time is reduced to the half of the or...

A novel algorithm for the lossless compression of hyperspectral sounding data is presented. The algorithm rests upon an efficient technique for three-dimensional image band reordering. The technique is based on a correlation factor. The correlation-based band ordering gives 5% higher compression ratios than natural ordering does. On the other hand,...

We present the implementation of a lossless hyperspectral image compression method for novel parallel environments. The method is an interband version of a linear prediction approach for hyperspectral images. The interband linear prediction method consists of two stages: predictive decorrelation that produces residuals and the entropy coding of the...

Image compression of hyperspectral sounder data is necessary because of the large storage requirements. The main objective of this paper is to present an efficient method for prediction coefficient estimation. The estimation is performed on a subset of the all image data points. The compression ratio remains almost the same with our method, at the...

An efficient lossless compression algorithm for 3D sounding data is presented. Major phases of the algorithm are: image band reordering, prediction an d coding. Proposed prediction technique allows expl oiting the data redundancy in both spectral and spatial dimens ions. In order to increase the efficiency of the pr ediction technique, image bands...

A clustered differential pulse code modulation lossless compression method for hyperspectral images is presented. The spectra of a hyperspectral image is clustered, and an optimized predictor is calculated for each cluster. Prediction is performed using a linear predictor. After prediction, the difference between the predicted and original values i...

In this paper, two new methods for edge detection in multispectral images are presented. They are based on the use of the self-organizing map (SOM) and a grayscale edge detector. With the 2-dimensional SOM the ordering of pixel vectors is obtained by applying the Peano scan, whereas this can be omitted using the 1-dimensional SOM. It is shown that...

This paper presents the implementation of a new method for lossless compression of hyperspectral images for novel parallel environments. The method in question is an interband version of the linear prediction approach for hyperspectral images. The interband linear prediction method consists of two stages: predictive decorrelation that produces resi...

This study proposes an interband version of the linear prediction approach for hyperspectral images. Linear prediction represents one of the best performing and most practical and general purpose lossless image compression techniques known today. The interband linear prediction method consists of two stages: predictive decorrelation producing resid...

This paper proposes an improvement to an interband version of the linear prediction approach for lossless compression of hyperspectral images. The improvements consisted of the use of non-predictable bands and the varied size of the sample set. Our improved method achieved an average compression ratio of 3.19 using 13 Airborne Visible/Infrared Imag...

Methods for noise reduction in multicomponent spectral images are developed and discussed. Multicomponent spectral images can be corrupted by noise either on all the channels or on some of the channels only. In the first case there are two possibilities: either the noise is on all the channels in the same way or the noise is randomly distributed on...

In this paper, a new group of noise reduction methods for multispectral images is presented. First, a 1-dimensional Self-Organizing Map (SOM) is taught using the pixel vectors of the noisy multispectral image. Then, a gray-level index image is formed containing the indexes of the SOM vectors. Several gray-level noise reduction methods are applied t...

Vector quantization (VQ) is an essential tool in signal processing. Although many algorithms for vector quantizer design have been developed, the classical generalized Lloyd algorithm (GLA) is still widely used, mainly for its simplicity and relatively good performance. Using law of cosines this letter presents a simple improved method for nearest-...

Remote sensing produces large amounts of digital data that is collected into databases. Since a variety of applications utilize multispectral data, the data cannot be compressed with lossy methods for some user communities. In this paper, we propose improvements for the combination of two reversible methods for the lossless compression of multispec...

This paper introduces a concept of positioning deviation compensation of a large scale flexible hydraulic manipulator by integrating a machine vision system and applying neural networks. The method has the advantage of being able to apply simple geometry based rigid inverse kinematic models in high precision flexible applications. Basically the met...

Deflection compensation of flexible boom structures in robot positioning is becoming an important part of machine automation. Positioning is usually done using tables containing the magnitude of the deflection with inverse kinematics solutions of a rigid manipulator. In this paper, a method for locating the tip of a flexible manipulator using machi...

In this paper, we present a modification to the back end of vector quantization (VQ), which improves the compression ratio of the lossless compression of multispectral images. By introducing a small change to the back end of VQ, the com-pression ratio improve significantly. In our expreriments, im-ages were compressed from the original image entrop...

A Fundamental activity in vector quantization involves searching a set of n k-dimensional data to find the nearest one. We present a fast algorithm that is full-search equivalent, i.e. the match is as good as the one that could be found using exhaustive search. The proposed method utilizes law of cosines to calculate an estimate for distance, which...

Thesis for the degree of Doctor of Science at Lappeenranta University of Technology, Lappeenranta, Finland 2003. Includes bibliographical references.