Digital Climate Modeling Manager

Job Overview The Digital Climate Modeling Manager is responsible for building, managing, and optimizing the climate modeling system of an enterprise or research institution. This involves utilizing high-performance computing (HPC), satellite remote sensing, AI models, meteorological data, and environmental monitoring networks to simulate climate change trends, predict extreme weather events, assess carbon emission impacts, and provide quantifiable and scientific support for decision-making. This position plays a crucial role in addressing climate change, formulating policies, guiding industrial transformation, and assessing ecological impacts.

Key Responsibilities

1. Climate Model System Construction and Maintenance

Design, build, and maintain digital climate models, including atmospheric circulation models (GCM), regional climate models (RCM), and carbon cycle models.

Integrate multi-source data from satellites, sensors, ocean buoys, and ground stations to build high-precision climate simulation datasets.

Continuously optimize model structures to improve operational efficiency, computational accuracy, and predictive stability.

1. AI and Data Science-Driven Climate Analysis

Manage the application of machine learning/deep learning models in climate prediction, including aerosol analysis, surface temperature prediction, and precipitation prediction.

1. Enhance model robustness using AI-assisted model calibration and uncertainty analysis.

2. Develop climate risk indices, carbon emission models, and ecological impact assessment tools.

3. Extreme Weather and Climate Risk Prediction

Provide early warning recommendations to governments and businesses by simulating and predicting anomalous climate events (heavy rain, heat waves, droughts, sea-level changes, etc.).

Support risk quantification and scenario analysis in industries such as insurance, energy, urban planning, and agriculture.

1. Project Management and Cross-Departmental Collaboration

Lead interdisciplinary projects involving climate scientists, data engineers, AI modeling teams, and environmental policy experts.

Collaborate with government agencies, research institutions, and international organizations (such as IPCC-related teams) to promote model data sharing and research initiatives.

Responsible for project planning, technical roadmap design, budget management, and deliverables.

1. Data Standardization, Validation, and Quality Management

Develop data standards, model validation processes, and quality control indicators.

Regularly monitor model bias and perform bias correction and post-processing.

Ensure model output meets the accuracy requirements of research, policy, and commercial scenarios.

1. Strategy Support and Results Visualization

Convert complex climate model results into easily understandable reports, visualization dashboards, or interactive simulation platforms.

Provide scientific evidence for the company's climate strategy, zero-carbon roadmap, ESG strategy, and sustainable investment decisions.

Support climate scenario analysis for urban planning, energy system layout, and ecological restoration projects.

Qualifications

1. Education

Master's degree or above in climate science, atmospheric science, environmental engineering, geographic information science, computational science, or a related field; PhD preferred.

Background in climate modeling, remote sensing technology, or Earth system science is preferred.

1. Work Experience

5+ years of experience in climate modeling, scientific computing, remote sensing analysis, or meteorological data modeling.

Familiarity with GCM/RCM models (such as WRF, CESM, GFDL, EC-Earth, etc.) is strongly preferred. Candidates with experience in AI modeling, climate risk analysis, or carbon emission modeling are highly competitive.

1. Technical Skills

Proficient in Python, R, Fortran, Julia, or a climate modeling-specific language.

Familiar with climate data formats (NetCDF, GRIB) and processing tools (CDO, NCO).

Proficient in GIS and remote sensing image processing tools (such as Google Earth Engine).

Experience in high-performance computing (HPC), large-scale distributed computing, and cloud computing.

1. Soft Skills

Possess interdisciplinary communication skills and be able to translate complex scientific models into actionable solutions.

Strong organizational, leadership, and project management skills.

Good logical thinking, scientific rigor, and problem-solving abilities.

Role Highlights

Participate in core technologies and international projects addressing global climate change.

Opportunities to influence national policies, corporate strategies, and industry carbon neutrality pathways.

Interdisciplinary integration (AI + Environmental Science + Data Modeling), high technical content, and broad career prospects.