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Congratulations Dr. Ziqi Yin! Successful PhD Defense on Greenland Ice Sheet Surface Melt

Sat, 16 May 2026 00:00:00 +0000

We are incredibly proud to announce that Ziqi Yin has successfully defended his PhD dissertation today in the Department of Atmospheric and Oceanic Sciences (ATOC) at the University of Colorado Boulder.

Dissertation title: Advancing Understanding of Greenland Ice Sheet Surface Melt Using Physics-Based and Machine Learning Models

Defense committee: Dr. Aneesh Subramanian (advisor, CU Boulder), Dr. Alexandra Jahn (CU Boulder), Dr. Rajashree Tri Datta (Delft University of Technology), Dr. Adam Herrington (National Center for Atmospheric Research), and Dr. Jianwu Wang (University of Maryland, Baltimore County).

Research Overview

Ziqi’s doctoral work marks a major step forward in polar climate research, bridging advanced physically-coupled Earth system modeling with cutting-edge data science and deep learning. His research focuses on improving our understanding of Greenland Ice Sheet (GrIS) mass loss — specifically surface melt, which has emerged as the dominant contributor to Greenland’s ice sheet degradation and subsequent global sea level rise in recent decades.

His dissertation consists of three core research thrusts:

1. Topographic Resolution Matters in Long-Term Projections (Published in the Journal of Advances in Modeling Earth Systems, JAMES)

Ziqi investigated how atmospheric grid resolution impacts century-scale ice sheet simulations. Using a variable-resolution (VR) grid featuring a ¼° regional refinement over the Arctic within the fully coupled CESM2.2–CISM2.1 framework, he demonstrated that conventional 1° coarse models flatten Greenland’s steep coastal topography. This flattening artifact artificially accelerates the positive melt–albedo feedback. By accurately resolving the terrain, his refined grid projected a multi-century sea level rise contribution (831 mm by year 350) that is 20–40% smaller than traditional models, indicating that coarse-resolution models may be overestimating future sea level rise.

2. Disentangling Melt Drivers via Causal Discovery (Under review at Geophysical Research Letters)

Moving beyond traditional correlation metrics, Ziqi applied the PCMCI+ causal discovery algorithm to isolate direct physical causes of summer melt anomalies in the ablation zone. His work successfully identified net shortwave radiation (the melt–albedo feedback) and turbulent heat fluxes (sensible and latent heat) as the dominant contemporaneous drivers of monthly summer melt anomalies. Under late-century high-warming scenarios (SSP3-7.0), he found that turbulent heat links become undirected, indicating a transition toward a more tightly synchronous and intensely coupled surface–atmosphere regime.

3. Accelerating Climate Projections with Graph Transformers (In preparation for The Cryosphere)

Ziqi developed a novel machine learning spatial emulator using a hybrid Graph Transformer architecture that combines local message passing with global self-attention. Trained on the 100-member CESM2 Large Ensemble (LENS2), the emulator faithfully replicates complex annual spatial melt fields under various climate conditions with an R² score above 0.99 and a root-mean-square error below 10%. When deployed across available CMIP6 models, it projects a surface melt increase of 89% (under low-emission SSP1-2.6) to 267% (under high-emission SSP5-8.5) by end of century. Under high-emission scenarios, Greenland’s northern basins are projected to experience the strongest acceleration in melting and eventually become the largest regional contributors to mass loss.

Impact

By combining the predictive power of variable-resolution climate physics, causal graphs, and spatial machine learning emulators, Ziqi’s work provides the scientific community with highly efficient, robust tools to track ice sheet–atmosphere interactions. These frameworks open new pathways for fast uncertainty quantification, risk assessments, and the identification of potential climate tipping points.

Please join us in extending our warmest congratulations to Dr. Ziqi Yin on this stellar milestone and wishing him all the best in his future scientific career!

Dr. Timothy Higgins Launches Operational AI-Based Ensemble Forecasting System for West Coast Atmospheric Rivers

Sat, 16 May 2026 00:00:00 +0000

Accurate probabilistic forecasting of extreme weather events is critical for water management and disaster preparedness along the U.S. West Coast. We are excited to share that postdoctoral research associate and climate fellow Dr. Timothy B. Higgins has successfully developed and operationalized a cutting-edge, diffusion-based ensemble forecasting system for Integrated Vapor Transport (IVT).

The model — the culmination of the final chapter of Dr. Higgins’ dissertation — is now officially live and operational at the Center for Western Weather and Water Extremes (CW3E).

Bridging the Gap in Probabilistic Forecasting

Traditional ensemble forecasting systems are computationally expensive, often limiting the number of scenarios meteorologists can simulate in real time. Dr. Higgins’ diffusion model fundamentally shifts this paradigm, demonstrating an ability to generate realistic 1,000-member ensembles within a highly manageable timeframe.

The model exhibits exceptional probabilistic forecasting skill, comparing favorably against premier global standards including the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF IFS) and the Global Ensemble Forecast System (GEFS).

A Collaborative Effort

This work began during Dr. Higgins’ time in the Advanced Study Program (ASP) Graduate Visitor Program at the National Center for Atmospheric Research (NCAR), where he worked closely with William Chapman. The project was co-authored alongside Dr. Aneesh Subramanian (University of Colorado Boulder) and Dr. Luca Delle Monache (CW3E / Scripps Institution of Oceanography).

View the Live Model

While the formal manuscript is currently under peer review, the real-time model outputs are already publicly accessible:

Congratulations to Tim and the entire team on moving this impactful AI-driven climate research from theory into active operations!

Applications Open: FERS Summer School on AI and Machine Learning for Earth System Modeling and Prediction

Wed, 22 Apr 2026 00:00:00 +0000

Applications are now open for the FERS Summer School on AI and Machine Learning for Earth System Modeling and Prediction, co-directed by Prof. Aneesh Subramanian and Prof. Will Chapman (University of Colorado Boulder).

This intensive summer school, organized by the CMCC Foundation’s Future Earth Research School (FERS), brings together early-career researchers to explore the latest advances in machine learning and artificial intelligence for climate science and Earth system modeling.

Dates: 8 – 19 June 2026

Location: Bertinoro (FC), Italy

Application deadline: May 3, 2026

For full details on the curriculum, dates, location, eligibility, and how to apply, visit the course page:

Luke Howard Defends His PhD Thesis

Mon, 06 Apr 2026 00:00:00 +0000

Congratulations to Lucas (Luke) Howard on defending his PhD dissertation today!

Title: Advancing Earth System Data Assimilation and Prediction with Probabilistic Machine Learning

Date: Monday, April 6, 2026, 10:00 AM MT

Location: SEEC N128

Abstract

Probabilistic machine learning methods offer significant potential for advancing earth system prediction, but existing applications have largely been deterministic, limiting their utility in contexts where uncertainty quantification is essential. This dissertation advances probabilistic machine learning for earth system prediction across three distinct but complementary applications, each targeting a persistent bottleneck in operational forecasting or data assimilation.

In the first application, a probabilistic U-Net-based neural network is developed for subseasonal marine heatwave forecasting in the northern Indian Ocean and Arabian Sea. The model produces skillful probabilistic forecasts at lead times of up to 10 weeks, outperforming persistence and climatology benchmarks across a range of deterministic and probabilistic skill metrics and performing comparably to or better than the ECMWF S2S dynamical forecast. The results suggest that planetary waves and low-frequency ocean dynamics provide windows of predictability that a probabilistic machine learning approach can exploit.

In the second application, a convolutional neural network is used to augment an ensemble Kalman filter for the assimilation of high-resolution observations that would otherwise be discarded due to computational constraints. Demonstrated as a proof-of-concept on the Lorenz-96 system, the augmented method reduces analysis error by 37% compared to an ensemble Kalman filter operating on spatially thinned observations alone, and produces more accurate and reliable ensemble forecasts at lead times of up to 10 days.

In the third application, a probabilistic neural network emulator of the Community Radiative Transfer Model is developed for the GOES Advanced Baseline Imager. The emulator matches the accuracy of the full physics-based model at a fraction of the computational cost, while generating reliable uncertainty estimates that could improve observation error characterization in data assimilation systems. Explainable AI methods applied across the second and third applications confirm that the trained networks extract physically meaningful information, increasing confidence in their reliability on out-of-sample data.

We are proud of Luke’s contributions to the group and wish him all the best in his next chapter!

Physics-Based Versus AI Weather Prediction Models: A Comparative Performance Assessment of Atmospheric River Prediction

Sat, 14 Feb 2026 00:00:00 +0000

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Adaptive Sampling of the Upper Ocean by Autonomous Floats during Atmospheric River precipitation

Thu, 01 Jan 2026 00:00:00 +0000

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Data-Driven Probabilistic Air-Sea Flux Parameterization

Thu, 01 Jan 2026 00:00:00 +0000

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Evaluating a Hybrid Ensemble Data Assimilative coupled Physical-Biogeochemical Ecosystem Model of the Red Sea

Thu, 01 Jan 2026 00:00:00 +0000

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Identifying Energy Balance Drivers of Greenland Ice Sheet Surface Melt Using Causal Discovery

Thu, 01 Jan 2026 00:00:00 +0000

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Impacts of Air-sea Coupling on Systematic Errors in Medium-Range Winter Forecasts over the North Pacific and North Atlantic

Thu, 01 Jan 2026 00:00:00 +0000

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Marine Heatwaves in the Arabian Sea: Drivers and Impacts on Atmospheric Circulation and Extreme Precipitation

Thu, 01 Jan 2026 00:00:00 +0000

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Modulation of tropical cyclone intensity by current–wind interaction

Thu, 01 Jan 2026 00:00:00 +0000

New Climate Change Center of Saudi Arabia: Advancing Understanding and Prediction for the Arabian Peninsula Climate

Thu, 01 Jan 2026 00:00:00 +0000

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Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference

Thu, 01 Jan 2026 00:00:00 +0000

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Salinity-Driven Barrier Layer Dynamics in the Equatorial Pacific: An Observational and CMIP6 Analysis

Thu, 01 Jan 2026 00:00:00 +0000

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Sensitivity of the 2023 Asian Summer Monsoon water vapor transport to Arabian Sea surface temperature anomalies

Thu, 01 Jan 2026 00:00:00 +0000

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Skillful Subseasonal Marine Heat Wave Forecasts using a Neural Network

Thu, 01 Jan 2026 00:00:00 +0000

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Subsurface Marine Heat Waves and Coral Bleaching in the Southern Red Sea Linked to Remote Forcing

Thu, 01 Jan 2026 00:00:00 +0000

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The Modification of Air-Sea Fluxes by Quasi-Periodic Sea Surface Temperature Structures in a Cross-Gradient Scenario

Thu, 01 Jan 2026 00:00:00 +0000

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Subsurface marine heat waves and coral bleaching in the southern red sea linked to remote forcing

Sun, 01 Jun 2025 00:00:00 +0000

Toward an integrated pantropical ocean observing system

Sat, 01 Feb 2025 00:00:00 +0000

Building Machine Learning Challenges for Anomaly Detection in Science

Wed, 01 Jan 2025 00:00:00 +0000

Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift

Wed, 01 Jan 2025 00:00:00 +0000

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Correlation to Causation: A Causal Deep Learning Framework for Arctic Sea Ice Prediction

Wed, 01 Jan 2025 00:00:00 +0000

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Correlation to Causation: A Causal Deep Learning Framework for Arctic Sea Ice Prediction

Wed, 01 Jan 2025 00:00:00 +0000

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Earth, Wind, and Fire: Are Boulder’s Extreme Downslope Winds Changing?

Wed, 01 Jan 2025 00:00:00 +0000

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Engaging K-12 Learners in Data Annotation for AI Climate Models

Wed, 01 Jan 2025 00:00:00 +0000

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Evaluating a Hybrid Ensemble Data Assimilative coupled Physical-Biogeochemical Ecosystem Model of the Red Sea

Wed, 01 Jan 2025 00:00:00 +0000

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Koopman operator theory for enhanced Pacific SST forecasting

Wed, 01 Jan 2025 00:00:00 +0000

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New Climate Change Center of Saudi Arabia: Advancing Understanding and Prediction for the Arabian Peninsula Climate

Wed, 01 Jan 2025 00:00:00 +0000

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The fate of Greenland Ice Sheet supraglacial lakes in a warm and cool year

Wed, 01 Jan 2025 00:00:00 +0000

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Enhanced regional ocean ensemble data assimilation through atmospheric coupling in the SKRIPS model

Tue, 01 Oct 2024 00:00:00 +0000

Subseasonal Potential Predictability of Horizontal Water Vapor Transport and Precipitation Extremes in the North Pacific

Sat, 01 Jun 2024 00:00:00 +0000

Causal Analysis Discovers an Enhanced Impact of Tropical Western Pacific on Indian Summer Monsoon Subseasonal Anomalies

Wed, 01 May 2024 00:00:00 +0000

Advancing Atmospheric River Science and Inspiring Future Development of the Atmospheric River Reconnaissance Program

Mon, 01 Jan 2024 00:00:00 +0000

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Enhanced Regional Ocean Ensemble Data Assimilation Through Atmospheric Coupling in the SKRIPS Model

Mon, 01 Jan 2024 00:00:00 +0000

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Greenland Ice Sheet wide supraglacial lake evolution and dynamics: insights from the 2018 and 2019 melt seasons

Mon, 01 Jan 2024 00:00:00 +0000

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Impact of atmospheric rivers on Arctic sea ice variations

Mon, 01 Jan 2024 00:00:00 +0000

Time Series Classification of Supraglacial Lakes Evolution over Greenland Ice Sheet

Mon, 01 Jan 2024 00:00:00 +0000

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Towards Kriging-informed Conditional Diffusion for Regional Sea-Level Data Downscaling: A Summary of Results

Mon, 01 Jan 2024 00:00:00 +0000

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Increase in MJO predictability under global warming

Fri, 01 Dec 2023 00:00:00 +0000

Subseasonal Prediction of Impactful California Winter Weather in a Hybrid Dynamical‐Statistical Framework

Wed, 01 Nov 2023 00:00:00 +0000

Balancing Volume, Temperature, and Salinity Budgets During 2014–2018 in the Tropical Pacific Ocean State Estimate

Thu, 01 Jun 2023 00:00:00 +0000

A Machine Learning Augmented Data Assimilation Method for High-Resolution Observation

Sun, 01 Jan 2023 00:00:00 +0000

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A variational Bayesian approach for ensemble filtering of stochastically parametrized systems

Sun, 01 Jan 2023 00:00:00 +0000

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Assessing the Impact of Ocean In Situ Observations on MJO Propagation Across the Maritime Continent in ECMWF Subseasonal Forecasts

Sun, 01 Jan 2023 00:00:00 +0000

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Development of a Statistical Subseasonal Forecast Tool to Predict California Atmospheric Rivers and Precipitation Based on MJO and QBO Activity

Sun, 01 Jan 2023 00:00:00 +0000

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Eddy-Mediated Mixing of Oxygen in the Equatorial Pacific

Sun, 01 Jan 2023 00:00:00 +0000

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Impacts of Northeastern Pacific Buoy Surface Pressure Observations

Sun, 01 Jan 2023 00:00:00 +0000

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Multi-Model Subseasonal Prediction Skill Assessment of Water Vapor Transport Associated With Atmospheric Rivers Over the Western US

Sun, 01 Jan 2023 00:00:00 +0000

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Observed and projected changes in snow accumulation and snowline in California's snowy mountains

Sun, 01 Jan 2023 00:00:00 +0000

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Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference

Sun, 01 Jan 2023 00:00:00 +0000

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Quantifying Causes of Arctic Amplification via Deep Learning Based Time-Series Causal Inference

Sun, 01 Jan 2023 00:00:00 +0000

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Reducing Uncertainty in Sea-level Rise Prediction: A Spatial-variability-aware Approach

Sun, 01 Jan 2023 00:00:00 +0000

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Reducing Uncertainty in Sea-level Rise Prediction: A Spatial-Variability-Aware Approach

Sun, 01 Jan 2023 00:00:00 +0000

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Signals of northward propagating monsoon intraseasonal oscillations (MISOs) in the RegCM4.7 CORDEX-CORE simulation over South Asia domain

Sun, 01 Jan 2023 00:00:00 +0000

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STint: Self-supervised Temporal Interpolation for Geospatial Data

Sun, 01 Jan 2023 00:00:00 +0000

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Subseasonal prediction of impactful California weather in a hybrid dynamical-statistical framework

Sun, 01 Jan 2023 00:00:00 +0000

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Subseasonal prediction of impactful California weather in a hybrid dynamical-statistical framework

Sun, 01 Jan 2023 00:00:00 +0000

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Using Deep Learning for an Analysis of Atmospheric Rivers in a High-Resolution Large Ensemble Climate Data Set

Sun, 01 Jan 2023 00:00:00 +0000

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Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu

Sun, 01 Jan 2023 00:00:00 +0000

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Atmospheric River Reconnaissance 2021: A Review

Wed, 01 Jun 2022 00:00:00 +0000

Annual Modulation of Diurnal Winds in the Tropical Oceans

Sat, 01 Jan 2022 00:00:00 +0000

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Atmospheric River Reconnaissance Workshop Promotes Research and Operations Partnership

Sat, 01 Jan 2022 00:00:00 +0000

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Focused Observations for Expanded Comprehension: Advancing Tropical Pacific Coupled Modeling and Process Understanding

Sat, 01 Jan 2022 00:00:00 +0000

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Focusing and Defocusing of Tropical Cyclone Generated Waves by Ocean Current Refraction

Sat, 01 Jan 2022 00:00:00 +0000

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Insights into the quantification and reporting of model-related uncertainty across different disciplines

Sat, 01 Jan 2022 00:00:00 +0000

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Overcoming the Challenges of Ocean Data Uncertainty

Sat, 01 Jan 2022 00:00:00 +0000

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Probabilistic Predictions from Deterministic Atmospheric River Forecasts with Deep Learning

Sat, 01 Jan 2022 00:00:00 +0000

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Weakening of Indian Summer Monsoon Synoptic Activity in Response to Polar Sea Ice Melt Induced by Albedo Reduction in a Climate Model

Sat, 01 Jan 2022 00:00:00 +0000

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Winter wet-dry weather patterns driving atmospheric rivers and Santa Ana winds provide evidence for increasing wildfire hazard in California

Sat, 01 Jan 2022 00:00:00 +0000

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Bay of Bengal Intraseasonal Oscillations and the 2018 Monsoon Onset

Fri, 01 Jan 2021 00:00:00 +0000

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Data Gaps within Atmospheric Rivers over the Northeastern Pacific

Fri, 01 Jan 2021 00:00:00 +0000

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Enhancing ensemble data assimilation into one-way-coupled models with one-step-ahead smoothing

Fri, 01 Jan 2021 00:00:00 +0000

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Improved Forecast Skill Through the Assimilation of Dropsonde Observations From the Atmospheric River Reconnaissance Program

Fri, 01 Jan 2021 00:00:00 +0000

Initialized Earth System prediction from subseasonal to decadal timescales

Fri, 01 Jan 2021 00:00:00 +0000

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Monthly Modulations of ENSO Teleconnections: Implications for Potential Predictability in North America

Fri, 01 Jan 2021 00:00:00 +0000

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The Role of Air-Sea Interactions in Atmospheric Rivers: Case Studies Using the SKRIPS Regional Coupled Model

Fri, 01 Jan 2021 00:00:00 +0000

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Towards an End-to-End Analysis and Prediction System for Weather, Climate, and Marine Applications in the Red Sea

Fri, 01 Jan 2021 00:00:00 +0000

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Towards implementing artificial intelligence post-processing in weather and climate: proposed actions from the Oxford 2019 workshop

Fri, 01 Jan 2021 00:00:00 +0000

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Tropical Pacific Air-Sea Interaction Processes and Biases in CESM2 and Their Relation to El Nino Development

Fri, 01 Jan 2021 00:00:00 +0000

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Uncertainty Quantification and Bayesian Inference of Cloud Parameterization in the NCAR Single Column Community Atmosphere Model (SCAM6)

Fri, 01 Jan 2021 00:00:00 +0000

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A Road Map to IndOOS-2: Better Observations of the Rapidly Warming Indian Ocean

Sun, 01 Nov 2020 00:00:00 +0000

A Reliability Budget Analysis of CESM-DART

Wed, 01 Jan 2020 00:00:00 +0000

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Estimation and prediction of the upper ocean circulation in the Bay of Bengal

Wed, 01 Jan 2020 00:00:00 +0000

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Forecast Errors and Uncertainties in Atmospheric Rivers

Wed, 01 Jan 2020 00:00:00 +0000

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Four Atmospheric Circulation Regimes Over the North Pacific and Their Relationship to California Precipitation on Daily to Seasonal Timescales

Wed, 01 Jan 2020 00:00:00 +0000

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How Does El Nino-Southern Oscillation Change Under Global Warming-A First Look at CMIP6

Wed, 01 Jan 2020 00:00:00 +0000

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Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz `96 Model

Wed, 01 Jan 2020 00:00:00 +0000

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Seasonal-to-interannual prediction of North American coastal marine ecosystems: Forecast methods, mechanisms of predictability, and priority developments

Wed, 01 Jan 2020 00:00:00 +0000

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Tropical climate variability in the Community Earth System Model: Data Assimilation Research Testbed

Wed, 01 Jan 2020 00:00:00 +0000

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West Coast Forecast Challenges and Development of Atmospheric River Reconnaissance

Wed, 01 Jan 2020 00:00:00 +0000

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Improving Atmospheric River Forecasts With Machine Learning

Sun, 01 Sep 2019 00:00:00 +0000

A Sustained Ocean Observing System in the Indian Ocean for Climate Related Scientific Knowledge and Societal Needs

Sat, 01 Jun 2019 00:00:00 +0000

A Limited Role for Unforced Internal Variability in Twentieth-Century Warming

Tue, 01 Jan 2019 00:00:00 +0000

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A Stochastic Representation of Subgrid Uncertainty for Dynamical Core Development

Tue, 01 Jan 2019 00:00:00 +0000

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Composite physical-biological El Nino and La Nina conditions in the California Current System in CESM1-POP2-BEC

Tue, 01 Jan 2019 00:00:00 +0000

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Contributors

Tue, 01 Jan 2019 00:00:00 +0000

Coupled effects of ocean current on wind stress in the Bay of Bengal: Eddy energetics and upper ocean stratification

Tue, 01 Jan 2019 00:00:00 +0000

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El Nino-Like Physical and Biogeochemical Ocean Response to Tropical Eruptions

Tue, 01 Jan 2019 00:00:00 +0000

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ENSO Bimodality and Extremes

Tue, 01 Jan 2019 00:00:00 +0000

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Experimental Subseasonal-to-Seasonal (S2S) Forecasting of Atmospheric Rivers Over the Western United States

Tue, 01 Jan 2019 00:00:00 +0000

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Integrated Observations of Global Surface Winds, Currents, and Waves: Requirements and Challenges for the Next Decade

Tue, 01 Jan 2019 00:00:00 +0000

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Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction

Tue, 01 Jan 2019 00:00:00 +0000

Observational Needs Supporting Marine Ecosystems Modeling and Forecasting: From the Global Ocean to Regional and Coastal Systems

Tue, 01 Jan 2019 00:00:00 +0000

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Ocean Observations to Improve Our Understanding, Modeling, and Forecasting of Subseasonal-to-Seasonal Variability

Tue, 01 Jan 2019 00:00:00 +0000

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Predictability of US West Coast Ocean Temperatures is not solely due to ENSO

Tue, 01 Jan 2019 00:00:00 +0000

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Remote and local influences in forecasting Pacific SST: a linear inverse model and a multimodel ensemble study

Tue, 01 Jan 2019 00:00:00 +0000

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SKRIPS v1.0: a regional coupled ocean-atmosphere modeling framework (MITgcm-WRF) using ESMF/NUOPC, description and preliminary results for the Red Sea

Tue, 01 Jan 2019 00:00:00 +0000

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The Risks of Contracting the Acquisition and Processing of the Nation’s Weather and Climate Data to the Private Sector

Tue, 01 May 2018 00:00:00 +0000

Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Project Goals and Experimental Design

Mon, 01 Jan 2018 00:00:00 +0000

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Circulation Drivers of Atmospheric Rivers at the North American West Coast

Mon, 01 Jan 2018 00:00:00 +0000

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Improving Weather Forecast Skill through Reduced-Precision Data Assimilation

Mon, 01 Jan 2018 00:00:00 +0000

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Sensitivity Studies of the Red Sea Eddies Using Adjoint Method

Mon, 01 Jan 2018 00:00:00 +0000

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Sensitivity Studies of the Red Sea Eddies Using Adjoint Method

Mon, 01 Jan 2018 00:00:00 +0000

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Statistical Characteristics of Long-Term High-Resolution Precipitable Water Vapor Data at Darwin

Mon, 01 Jan 2018 00:00:00 +0000

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Statistical Characteristics of Long-Term High-Resolution Precipitable Water Vapor Data at Darwin

Mon, 01 Jan 2018 00:00:00 +0000

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Supplementary material to “Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Project Goals and Experimental Design”

Mon, 01 Jan 2018 00:00:00 +0000

The Risks of Contracting the Acquisition and Processing of the Nation's Weather and Climate Data to the Private Sector (vol 99, pg 869, 2018)

Mon, 01 Jan 2018 00:00:00 +0000

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GCMs With Full Representation of Cloud Microphysics and Their MJO Simulations

Tue, 01 Aug 2017 00:00:00 +0000

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A study of reduced numerical precision to make superparameterization more competitive using a hardware emulator in the OpenIFS model

Sun, 01 Jan 2017 00:00:00 +0000

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Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

Sun, 01 Jan 2017 00:00:00 +0000

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Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction

Sun, 01 Jan 2017 00:00:00 +0000

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Impact of stochastic physics on tropical precipitation in the coupled ECMWF model

Sun, 01 Jan 2017 00:00:00 +0000

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Maintaining Momentum in Climate Model Development

Sun, 01 Jan 2017 00:00:00 +0000

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Seasonal and decadal forecasts of Atlantic Sea surface temperatures using a linear inverse model

Sun, 01 Jan 2017 00:00:00 +0000

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Stochastic representations of model uncertainties at ECMWF: state of the art and future vision

Sun, 01 Jan 2017 00:00:00 +0000

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The role of wind gusts in upper ocean diurnal variability

Sun, 01 Jan 2017 00:00:00 +0000

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Simulation of High-Resolution Precipitable Water Data by a Stochastic Model with a Random Trigger

Fri, 01 Jan 2016 00:00:00 +0000

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The eddy kinetic energy budget in the Red Sea

Fri, 01 Jan 2016 00:00:00 +0000

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The physical oceanographic environment during the CCE-LTER Years: Changes in climate and concepts

Thu, 01 Jan 2015 00:00:00 +0000

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The skill of atmospheric linear inverse models in hindcasting the Madden-Julian Oscillation

Thu, 01 Jan 2015 00:00:00 +0000

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Coupled Impacts of the Diurnal Cycle of Sea Surface Temperature on the Madden-Julian Oscillation

Wed, 01 Jan 2014 00:00:00 +0000

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Diagnosing MJO hindcast biases in NCAR CAM3 using nudging during the DYNAMO field campaign

Wed, 01 Jan 2014 00:00:00 +0000

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Eddies in the Red Sea: A statistical and dynamical study

Wed, 01 Jan 2014 00:00:00 +0000

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The MJO and global warming: a study in CCSM4

Wed, 01 Jan 2014 00:00:00 +0000

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A data assimilative perspective of oceanic mesoscale eddy evolution during VOCALS-REx

Fri, 01 Mar 2013 00:00:00 +0000

An Adjoint-Based Adaptive Ensemble Kalman Filter

Tue, 01 Jan 2013 00:00:00 +0000

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Linear versus Nonlinear Filtering with Scale-Selective Corrections for Balanced Dynamics in a Simple Atmospheric Model

Sun, 01 Jan 2012 00:00:00 +0000

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The Madden-Julian Oscillation in CCSM4

Sat, 01 Jan 2011 00:00:00 +0000

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An Adaptive Approach to Mitigate Background Covariance Limitations in the Ensemble Kalman Filter

Fri, 01 Jan 2010 00:00:00 +0000

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