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DOE OSTI2021

Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures

Today's high-performance computing (HPC) applications are producing vast volumes of data, which are challenging to store and transfer efficiently during the execution, such that data compression is becoming a critical technique to mitigate the storage burden and data movement cost. Huffman coding is arguably the most efficient Entropy coding algorithm in information theory, such that it could be found as a fundamental step in many modern compression algorithms such as DEFLATE. On the other hand, today's HPC applications are more and more relying on the accelerators such as GPU on supercomputers, while Huffman encoding suffers from low throughput on GPUs, resulting in a significant bottleneck in the entire data processing. In this paper, we propose and implement an efficient Huffman encoding approach based on modern GPU architectures, which addresses two key challenges: (1) how to parallelize the entire Huffman encoding algorithm, including codebook construction, and (2) how to fully utilize the high memory-bandwidth feature of modern GPU architectures. The detailed contribution is fourfold. (1) We develop an efficient parallel codebook construction on GPUs that scales effectively with the number of input symbols. (2) We propose a novel reduction based encoding scheme that can efficiently merge the codewords on GPUs. (3) We optimize the overall GPU performance by leveraging the state-of-the-art CUDA APIs such as Cooperative Groups. (4) We evaluate our Huffman encoder thoroughly using six real-world application datasets on two advanced GPUs and compare with our implemented multi-threaded Huffman encoder. Experiments show that our solution can improve the encoding throughput by up to 5.0x and 6.8x on NVIDIA RTX 5000 and V100, respectively, over the state-of-the-art GPU Huffman encoder, and by up to 3.3x over the multi-thread encoder on two 28-core Xeon Platinum 8280 CPUs.

Tian, Jiannan↗

DOE OSTI2022

Competing Easy-Axis Anisotropies Impacting Magnetic Tunnel Junction-Based Molecular Spintronics Devices (MTJMSDs)

Molecular spintronics devices (MSDs) attempt to harness molecules’ quantum state, size, and configurable attributes for application in computer devices—a quest that began more than 70 years ago. In the vast number of theoretical studies and limited experimental attempts, MSDs have been found to be suitable for application in memory devices and futuristic quantum computers. MSDs have recently also exhibited intriguing spin photovoltaic-like phenomena, signaling their potential application in cost-effective and novel solar cell technologies. The molecular spintronics field’s major challenge is the lack of mass-fabrication methods producing robust magnetic molecule connections with magnetic electrodes of different anisotropies. Another main challenge is the limitations of conventional theoretical methods for understanding experimental results and designing new devices. Magnetic tunnel junction-based molecular spintronics devices (MTJMSDs) are designed by covalently connecting paramagnetic molecules across an insulating tunneling barrier. The insulating tunneling barrier serves as a mechanical spacer between two ferromagnetic (FM) electrodes of tailorable magnetic anisotropies to allow molecules to undergo many intriguing phenomena. Our experimental studies showed that the paramagnetic molecules could produce strong antiferromagnetic coupling between two FM electrodes, leading to a dramatic large-scale impact on the magnetic electrode itself. Recently, we showed that the Monte Carlo Simulation (MCS) was effective in providing plausible insights into the observation of unusual magnetic domains based on the role of single easy-axis magnetic anisotropy. Here, we experimentally show that the response of a paramagnetic molecule is dramatically different when connected to FM electrodes of different easy-axis anisotropies. Motivated by our experimental studies, here, we report on an MCS study investigating the impact of the simultaneous presence of two easy-axis anisotropies on MTJMSD equilibrium properties. In-plane easy-axis anisotropy produced multiple magnetic phases of opposite spins. The multiple magnetic phases vanished at higher thermal energy, but the MTJMSD still maintained a higher magnetic moment because of anisotropy. The out-of-plane easy-axis anisotropy caused a dominant magnetic phase in the FM electrode rather than multiple magnetic phases. The simultaneous application of equal-magnitude in-plane and out-of-plane easy-axis anisotropies on the same electrode negated the anisotropy effect. Our experimental and MCS study provides insights for designing and understanding new spintronics-based devices.

42 ENGINEERING↗

NASA NTRS1984

Holographic data storage crystals for LDEF (A0044)

Electro-optic holographic recording systems were developed. The spaceworthiness of electro-optic crystals for use in ultrahigh capacity space data storage and retrieval systems are examined. The crystals for this experiment are included with the various electro-optical components of LDEF experiment. The effects of long-duration exposure on active optical system components is investigated. The concept of data storage in an optical-phase holographic memory is illustrated.

Callen, W. R.↗

NASA NTRS1999

Study Design to Test the Hypothesis That Long-Term Space Travel Harms the Human and Animal Immune Systems

The potential threat of immunosuppression and abnormal inflammatory responses in long-term space travel, leading to unusual predilection for opportunistic infections, malignancy, and death, is of ma or concern to the National Aeronautics and Space Administration (NASA) Program. This application has been devised to seek answers to questions of altered immunity in space travel raised by previous investigations spanning 30-plus years. We propose to do this with the help of knowledge gained by the discovery of the molecular basis of many primary and secondary immunodeficiency diseases and by application of molecular and genetic technology not previously available. Two areas of immunity that previously received little attention in space travel research will be emphasized: specific antibody responses and non-specific inflammation and adhesion. Both of these areas of research will not only add to the growing body of information on the potential effects of space travel on the immune system, but be able to delineate any functional alterations in systems important for antigen presentation, specific immune memory, and cell:cell and cell:endothelium interactions. By more precisely defining molecular dysfunction of components of the immune system, it is hoped that targeted methods of prevention of immune damage in space could be devised.

Shearer, William T.↗

NASA NTRS2017

Computational and Experimental Fluid-Structure Interaction Analysis of a High-Lift Wing with a Slat-Cove Filler for Noise Reduction

Airframe noise is a significant component of overall noise produced by transport aircraft during landing and approach (low speed maneuvers). A significant source for this noise is the cove of the leading-edge slat. The slat-cove filler (SCF) has been shown to be effective at mitigating slat noise. The objective of this work is to understand the fluid-structure interaction (FSI) behavior of a superelastic shape memory alloy (SMA) SCF in flow using both computational and physical models of a high-lift wing. Initial understanding of flow around the SCF and wing is obtained using computational fluid dynamics (CFD) analysis at various angles of attack. A framework compatible with an SMA constitutive model (implemented as a user material subroutine) is used to perform FSI analysis for multiple flow and configuration cases. A scaled physical model of the high-lift wing is constructed and tested in the Texas A&M 3 ft-by-4-foot wind tunnel. Initial validation of both CFD and FSI analysis is conducted by comparing lift, drag and pressure distributions with experimental results.

Scholten, William D.↗

DOE OSTI2021

Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures

Today's high-performance computing (HPC) applications are producing vast volumes of data, which are challenging to store and transfer efficiently during the execution, such that data compression is becoming a critical technique to mitigate the storage burden and data movement cost. Huffman coding is arguably the most efficient Entropy coding algorithm in information theory, such that it could be found as a fundamental step in many modern compression algorithms such as DEFLATE. On the other hand, today's HPC applications are more and more relying on the accelerators such as GPU on supercomputers, while Huffman encoding suffers from low throughput on GPUs, resulting in a significant bottleneck in the entire data processing. In this paper, we propose and implement an efficient Huffman encoding approach based on modern GPU architectures, which addresses two key challenges: (1) how to parallelize the entire Huffman encoding algorithm, including codebook construction, and (2) how to fully utilize the high memory-bandwidth feature of modern GPU architectures. The detailed contribution is fourfold. (1) We develop an efficient parallel codebook construction on GPUs that scales effectively with the number of input symbols. (2) We propose a novel reduction based encoding scheme that can efficiently merge the codewords on GPUs. (3) We optimize the overall GPU performance by leveraging the state-of-the-art CUDA APIs such as Cooperative Groups. (4) We evaluate our Huffman encoder thoroughly using six real-world application datasets on two advanced GPUs and compare with our implemented multithreaded Huffman encoder. Experiments show that our solution can improve the encoding throughput by up to 5.0× and 6.8× on NVIDIA RTX 5000 and V100, respectively, over the state-of-the-art GPU Huffman encoder, and by up to 3.3× over the multithread encoder on two 28-core Xeon Platinum 8280 CPUs.

Tian, Jiannan↗

DOE OSTI2024

Hydrologic connectivity and dynamics of solute transport in a mountain stream: Insights from a long-term tracer test and multiscale transport modeling informed by machine learning

The movement of solutes in a watershed is a complex process with multiple interactions and feedbacks across spatial and temporal scales. Modeling the dynamics of solute transport along diverse hydrologic pathways within watersheds – from hillslopes to stream channels and in and out of the hyporheic zones – is challenging but critically important, as these processes integrate and contribute to the biogeochemical functioning of the river corridor up to the river network scale. Here we use results from a long-term network-scale tracer test at the H.J. Andrews experimental forest in western Cascade Mountains, Oregon, USA to inform a multiscale framework for transport in stream corridors. The framework uses a Lagrangian-based subgrid model to represent the effects of hyporheic exchange flow and advective transport at stream network scales. The spatially and temporally resolved stream discharge needed for the transport model is imputed across the river system by an entity-aware long short-term memory network. Modeled concentrations show good agreements with the observations and exhibit power scaling laws indicative of a very wide range of timescales over which hyporheic exchange flow occurs. Our results demonstrate a data-informed modeling framework that links dynamical processes occurring at small scales to a network context to help understand how changes at reach scale cascade into network-scale effects, providing a useful tool for sustainable river basin management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Scaling Effects in Perovskite Ferroelectrics: Fundamental Limits and Process-Structure-Property Relations

Ferroelectric materials are well-suited for a variety of applications because they can offer a combination of high performance and scaled integration. Examples of note include piezoelectrics to transform between electrical and mechanical energies, capacitors used to store charge, electro-optic devices, and non-volatile memory storage. Accordingly, they are widely used as sensors, actuators, energy storage, and memory components, ultrasonic devices, and in consumer electronics products. Because these functional properties arise from a non-centrosymmetric crystal structure with spontaneous strain and a permanent electric dipole, the properties depend upon physical and electrical boundary conditions, and consequently, physical dimension. The change of properties with decreasing physical dimension is commonly referred to as a size effect. In thin films, size effects are widely observed, while in bulk ceramics, changes in properties from the values of large-grained specimens is most notable in samples with grain sizes below several microns. It is important to note that ferroelectricity typically persists to length scales of about 10 nm, but below this point is often absent. Despite the stability of ferroelectricity for dimensions greater than ~10 nm, the dielectric and piezoelectric coefficients of scaled ferroelectrics are suppressed relative to their bulk counterparts, in some cases by changes up to 80%. The loss of extrinsic contributions (domain and phase boundary motion) to the electromechanical response accounts for much of this suppression. In this article the current understanding of the underlying mechanisms for this behavior in perovskite ferroelectrics are reviewed. We focus on the intrinsic limits of ferroelectric response, the roles of electrical and mechanical boundary conditions, grain size and thickness effects, and extraneous effects related to processing. Ultimately, in many cases, multiple mechanisms combine to produce the observed scaling effects.

36 MATERIALS SCIENCE↗

NASA NTRS2003

Quantum Search in Hilbert Space

A proposed quantum-computing algorithm would perform a search for an item of information in a database stored in a Hilbert-space memory structure. The algorithm is intended to make it possible to search relatively quickly through a large database under conditions in which available computing resources would otherwise be considered inadequate to perform such a task. The algorithm would apply, more specifically, to a relational database in which information would be stored in a set of N complex orthonormal vectors, each of N dimensions (where N can be exponentially large). Each vector would constitute one row of a unitary matrix, from which one would derive the Hamiltonian operator (and hence the evolutionary operator) of a quantum system. In other words, all the stored information would be mapped onto a unitary operator acting on a quantum state that would represent the item of information to be retrieved. Then one could exploit quantum parallelism: one could pose all search queries simultaneously by performing a quantum measurement on the system. In so doing, one would effectively solve the search problem in one computational step. One could exploit the direct- and inner-product decomposability of the unitary matrix to make the dimensionality of the memory space exponentially large by use of only linear resources. However, inasmuch as the necessary preprocessing (the mapping of the stored information into a Hilbert space) could be exponentially expensive, the proposed algorithm would likely be most beneficial in applications in which the resources available for preprocessing were much greater than those available for searching.

Zak, Michail↗

DOE OSTI2014

Effect of current compliance and voltage sweep rate on the resistive switching of HfO{sub 2}/ITO/Invar structure as measured by conductive atomic force microscopy

The electrical characterization of HfO{sub 2}/ITO/Invar resistive switching memory structure was studied using conductive atomic force microscopy (AFM) with a semiconductor parameter analyzer, Agilent 4156C. The metal alloy Invar was used as the metal substrate to ensure good ohmic contact with the substrate holder of the AFM. A conductive Pt/Ir AFM tip was placed in direct contact with the HfO{sub 2} surface, such that it acted as the top electrode. Nanoscale current-voltage (I-V) characteristics of the HfO{sub 2}/ITO/Invar structure were measured by applying a ramp voltage through the conductive AFM tip at various current compliances and ramp voltage sweep rates. It was found that the resistance of the low resistance state (RLRS) decreased with increasing current compliance value, but resistance of high resistance state (RHRS) barely changed. However, both the RHRS and RLRS decreased as the voltage sweep rate increased. The reasons for this dependency on current compliance and voltage sweep rate are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1990

Single-pass memory system evaluation for multiprogramming workloads

Modern memory systems are composed of levels of cache memories, a virtual memory system, and a backing store. Varying more than a few design parameters and measuring the performance of such systems has traditionally be constrained by the high cost of simulation. Models of cache performance recently introduced reduce the cost simulation but at the expense of accuracy of performance prediction. Stack-based methods predict performance accurately using one pass over the trace for all cache sizes, but these techniques have been limited to fully-associative organizations. This paper presents a stack-based method of evaluating the performance of cache memories using a recurrence/conflict model for the miss ratio. Unlike previous work, the performance of realistic cache designs, such as direct-mapped caches, are predicted by the method. The method also includes a new approach to the problem of the effects of multiprogramming. This new technique separates the characteristics of the individual program from that of the workload. The recurrence/conflict method is shown to be practical, general, and powerful by comparing its performance to that of a popular traditional cache simulator. The authors expect that the availability of such a tool will have a large impact on future architectural studies of memory systems.

Conte, Thomas M.↗

DOE OSTI2019

Single-Dose Vaccination with a Hepatotropic Adeno-associated Virus Efficiently Localizes T Cell Immunity in the Liver with the Potential To Confer Rapid Protection against Hepatitis C Virus

Hepatitis C virus (HCV) is a significant contributor to the global disease burden, and development of an effective vaccine is required to eliminate HCV infections worldwide. CD4 + and CD8 + T cell immunity correlates with viral clearance in primary HCV infection, and intrahepatic CD8 + tissue-resident memory T (T RM ) cells provide lifelong and rapid protection against hepatotropic pathogens. Consequently, we aimed to develop a vaccine to elicit HCV-specific CD4 + and CD8 + T cells, including CD8 + T RM cells, in the liver, given that HCV primarily infects hepatocytes. To achieve this, we vaccinated wild-type BALB/c mice with a highly immunogenic cytolytic DNA vaccine encoding a model HCV (genotype 3a) nonstructural protein (NS5B) and a mutant perforin (pVAX-NS5B-PRF), as well as a recombinant adeno-associated virus (AAV) encoding NS5B (rAAV-NS5B). A novel fluorescent target array (FTA) was used to map immunodominant CD4 + T helper (T H ) cell and cytotoxic CD8 + T cell epitopes of NS5B in vivo , which were subsequently used to design a K d NS5B 451-459 tetramer and analyze NS5B-specific T cell responses in vaccinated mice in vivo . The data showed that intradermal prime/boost vaccination with pVAX-NS5B-PRF was effective in eliciting T H and cytotoxic CD8 + T cell responses and intrahepatic CD8 + T RM cells, but a single intravenous dose of hepatotropic rAAV-NS5B was significantly more effective. As a T-cell-based vaccine against HCV should ideally result in localized T cell responses in the liver, this study describes primary observations in the context of HCV vaccination that can be used to achieve this goal. There are currently at least 71 million individuals with chronic HCV worldwide and almost two million new infections annually. Although the advent of direct-acting antivirals (DAAs) offers highly effective therapy, considerable remaining challenges argue against reliance on DAAs for HCV elimination, including high drug cost, poorly developed health infrastructure, low screening rates, and significant reinfection rates. Accordingly, development of an effective vaccine is crucial to HCV elimination. An HCV vaccine that elicits T cell immunity in the liver will be highly protective for the following reasons: (i) T cell responses against nonstructural proteins of the virus are associated with clearance of primary infection, and (ii) long-lived liver-resident T cells alone can protect against malaria infection of hepatocytes. Thus, in this study we exploit promising vaccination platforms to highlight strategies that can be used to evoke highly functional and long-lived T cell responses in the liver for protection against HCV.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1997

The Role of Global Hydrologic Processes in Interannual and Long-Term Climate Variability

The earth's climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation-- the major mode of interannual variability-- is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the "memory" of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth's climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being "data poor' has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.

Robertson, Franklin R.↗

DOE OSTI2023

Early-life atomic-bomb irradiation accelerates immunological aging and elevates immune-related intracellular reactive oxygen species

Reactive oxygen species (ROS) play an important role in immune responses; however, their excessive production and accumulation increases the risk of inflammation-related diseases. Although irradiation is known to accelerate immunological aging, the underlying mechanism is still unclear. To determine the possible involvement of ROS in this mechanism, we examined 10,023 samples obtained from 3752 atomic-bomb survivors in Hiroshima and Nagasaki, who participated in repeated biennial examinations from 2008 to 2016, for the effects of aging and radiation exposure on intracellular ROS (H 2 O 2 and O 2 •- ) levels, percentages of T-cell subsets, and the effects of radiation exposure on the relationship between cell percentages and intracellular ROS levels in T-cell subsets. The cell percentages and intracellular ROS levels in T-cell subsets were measured using flow cytometry, with both fluorescently labeled antibodies and the fluorescent reagents, carboxy-DCFDA and hydroethidine. The percentages of naïve CD4 + and CD8 + T cells decreased with increasing age and radiation dose, while the intracellular O 2 •- levels in central and effector memory CD8 + T cells increased. Additionally, when divided into three groups based on the percentages of naïve CD4 + T cells, intracellular O 2 •- levels of central and effector memory CD8 + T cells were significantly elevated with the lowest radiation dose group in the naïve CD4 + T cells. Thus, the radiation exposure-induced decrease in the naïve CD4 + T cell pool size may reflect decreased immune function, resulting in increased intracellular ROS levels in central and effector memory CD8 + T cells, and increased intracellular oxidative stress.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2015

Magnetoresistance of galfenol-based magnetic tunnel junction

The manipulation of ferromagnetic layer magnetization via electrical pulse is driving an intense research due to the important applications that this result will have on memory devices and sensors. In this study we realized a magnetotunnel junction in which one layer is made of Galfenol (Fe{sub 1-x}Ga{sub x}) which possesses one of the highest magnetostrictive coefficient known. The multilayer stack has been grown by molecular beam epitaxy and e-beam evaporation. Optical lithography and physical etching have been combined to obtain 20x20 micron sized pillars. The obtained structures show tunneling conductivity across the junction and a tunnel magnetoresistance (TMR) effect of up to 11.5% in amplitude.

36 MATERIALS SCIENCE↗

DOE OSTI2018

On the fast kinetics of B2–L2 1 ordering in Ni-Co-Mn-In metamagnetic shape memory alloys

B2–L2 1 configurational order resulting from thermal processing of Ni-Co-Mn-In Heusler alloys is one of the main factors defining the characteristics of the martensitic transformation experienced by these alloys. While the effects of the quenched-in disorder on the martensitic transformation have been extensively investigated, the kinetics of the ordering process is not well known and mostly inferred from the indirect results such as the dependence of the martensitic transformation or magnetic transition temperatures to thermal processing. However, recent results suggested that the kinetics of B2– L 2 1 ordering could have a more significant role than expected in the final state of the material and its functional properties. In the current work, an attempt has been made to investigate the kinetics of B2–L2 1 ordering in order to evaluate the dependence of the quenched-in disorder on the different variables of the thermal procedures. Results showed that ordering rate has a strong dependence on annealing temperature. Below 600 K, slow kinetics is forcing the crystal to always contain a certain amount of quenched-in disorder at room temperature. Between 600 K and 750 K, kinetics is fast enough to reach thermal equilibrium state within tens of minutes during the annealing process. Above 750 K, kinetics is very fast and thermal equilibrium can be reached during heating, so no isothermal holding is required. Furthermore, these predictions have been confirmed using differential scanning calorimetry and in-situ high-energy X-Ray diffraction measurements for non-direct estimations of the degree of order.

36 MATERIALS SCIENCE↗

DOE OSTI2014

TH-A-19A-12: A GPU-Accelerated and Monte Carlo-Based Intensity Modulated Proton Therapy Optimization System

Purpose: To develop a clinically applicable intensity modulated proton therapy (IMPT) optimization system that utilizes more accurate Monte Carlo (MC) dose calculation, rather than analytical dose calculation. Methods: A very fast in-house graphics processing unit (GPU) based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified gradient based optimization method was used to achieve the desired dose volume histograms (DVH). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve the spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that Result from maintaining the intrinsic CT resolution and large number of proton spots. The dose effects were studied particularly in cases with heterogeneous materials in comparison with the commercial treatment planning system (TPS). Results: For a relatively large and complex three-field bi-lateral head and neck case (i.e. >100K spots with a target volume of ∼1000 cc and multiple surrounding critical structures), the optimization together with the initial MC dose influence map calculation can be done in a clinically viable time frame (i.e. less than 15 minutes) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The DVHs of the MC TPS plan compare favorably with those of a commercial treatment planning system. Conclusion: A GPU accelerated and MC-based IMPT optimization system was developed. The dose calculation and plan optimization can be performed in less than 15 minutes on a hardware system costing less than 45,000 dollars. The fast calculation and optimization makes the system easily expandable to robust and multi-criteria optimization. This work was funded in part by a grant from Varian Medical Systems, Inc.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2016

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).

58 GEOSCIENCES↗