Earth System Modeling Platforms And Governance Centralization

1. Introduction

Earth System Modeling (ESM) platforms are computational systems used to model interactions among the atmosphere, oceans, land, ice, ecosystems, carbon cycles, energy systems and human activities. Modern ESM platforms increasingly combine climate models, satellite data, artificial intelligence, digital twins, high-performance computing, cloud infrastructure and large environmental datasets.

The competition-law concern arises when a small number of undertakings control the computational infrastructure, datasets, models, interfaces, standards or decision-making systems through which Earth-system information is produced and used.

This can create governance centralization: a situation in which private or public-private platforms acquire the practical ability to determine who obtains environmental data, which models are accepted, how risks are measured, what standards are followed and which technological providers can participate.

The issue therefore lies at the intersection of:

competition law;

digital-platform regulation;

data governance;

environmental regulation;

public procurement;

infrastructure regulation;

AI governance;

essential-facilities doctrine;

interoperability;

algorithmic transparency; and

public-law accountability.

2. Meaning of Earth System Modeling Platforms

An Earth System Modeling platform may contain several interconnected layers:

A. Data layer

It collects:

satellite observations;

weather information;

ocean measurements;

biodiversity data;

geological information;

emissions data;

land-use information;

sensor data; and

socioeconomic datasets.

B. Modeling layer

Models process this information to predict or simulate:

climate change;

extreme weather;

sea-level rise;

carbon cycles;

water availability;

agricultural conditions;

ecosystem changes;

pollution;

energy demand; and

environmental risks.

C. Computational layer

Large models require:

supercomputers;

cloud infrastructure;

GPUs;

specialized AI accelerators;

storage;

networking infrastructure; and

high-performance computing services.

D. Platform layer

A platform may provide:

APIs;

model libraries;

data repositories;

simulation environments;

visualization tools;

digital twins;

AI interfaces; and

prediction services.

E. Governance layer

The most important competition issue arises when the platform also determines:

access rules;

technical standards;

model-validation procedures;

data-sharing requirements;

interoperability;

ranking systems;

certification;

pricing;

procurement conditions; and

participation in the ecosystem.

The platform can consequently move from being merely a technology provider to becoming a quasi-governance institution.

3. What Is Governance Centralization?

Governance centralization occurs where decision-making concerning an important technological ecosystem becomes concentrated in one undertaking, a small group of undertakings, or a tightly coordinated public-private structure.

For Earth-system modeling, centralization can occur at several levels.

3.1 Data centralization

One platform may become the principal gateway to environmental datasets.

3.2 Computational centralization

A limited number of cloud or HPC providers may possess the computational capacity necessary to run sophisticated models.

3.3 Model centralization

A particular model or model family may become an industry standard.

3.4 Interface centralization

Researchers and government agencies may become dependent upon one API or software environment.

3.5 Standards centralization

One platform may effectively determine technical standards.

3.6 Decision centralization

The most serious problem occurs when public authorities rely upon one private platform for environmental decisions.

This may give the platform indirect influence over:

infrastructure planning;

disaster preparation;

insurance;

agriculture;

energy;

carbon markets;

urban planning; and

environmental compliance.

4. Competition-Law Theory

The fundamental competition-law question is not simply:

"Is the platform large?"

Instead, the question is:

Has control over Earth-system modeling infrastructure become sufficiently concentrated that competitors, governments, researchers or downstream users cannot realistically operate without access to it?

Several competition doctrines become relevant.

5. Relevant Market Definition

Potential relevant markets may include:

Earth-system modeling software;

climate-modeling platforms;

environmental data services;

environmental cloud computing;

climate-risk analytics;

digital-twin platforms;

environmental AI services;

satellite-data processing;

high-performance environmental computing;

environmental prediction APIs.

The market should not automatically be defined as the enormous market for "technology."

A narrow market may exist where customers cannot reasonably substitute one platform for another.

6. Network Effects

Earth-system modeling platforms can exhibit strong network effects.

More users can generate:

more data;

more model improvements;

more validation;

more applications;

more interoperability;

more developer participation.

That can produce a feedback loop:

More users → more data → better models → more users → greater market power.

Eventually, competing platforms may struggle to reach sufficient scale.

7. Data Advantages

Environmental data can become a major competitive asset.

A platform with exclusive access to:

historical climate datasets;

high-resolution satellite imagery;

sensor networks;

proprietary environmental observations;

real-time weather information;

may obtain a substantial advantage over competitors.

The competitive concern becomes stronger where the undertaking:

controls an indispensable dataset;

refuses access;

prevents interoperability;

combines the data with other services; and

uses the data to strengthen downstream dominance.

8. Essential-Facilities Concerns

The essential-facilities doctrine becomes relevant where competitors cannot reasonably compete without access to infrastructure controlled by a dominant undertaking.

In the Earth-system context, possible facilities include:

unique datasets;

indispensable computational infrastructure;

environmental APIs;

model-validation infrastructure;

satellite-processing platforms;

interoperability interfaces.

However, merely being useful or commercially important does not necessarily make something an essential facility. Competition authorities normally require stringent conditions before compelling access.

9. Refusal to Deal

A dominant Earth-system platform could theoretically violate competition law if it:

terminates access to essential environmental data;

refuses interoperability;

denies API access selectively;

excludes competing model providers;

restricts access to computing resources; or

discriminates against downstream competitors.

The critical question is whether the refusal constitutes abusive exclusion rather than legitimate commercial conduct.

10. Self-Preferencing

Suppose an Earth-system platform operates both:

a modeling marketplace; and

its own proprietary climate model.

If the platform systematically gives its own model:

superior ranking;

faster processing;

privileged data;

better API access;

lower prices;

preferred certification;

it could create a self-preferencing problem.

This resembles competition concerns encountered in large digital platforms.

11. Vertical Integration

Vertical integration can occur when one company controls:

Data → Cloud → Computing → Model → API → Application → Government contract.

This structure can generate efficiencies, but it may also permit foreclosure.

For example:

A cloud provider acquires an environmental-modeling company and then makes its cloud infrastructure technically or financially preferable for running that model.

Competitors may then face higher costs.

12. Tying and Bundling

A dominant Earth-system platform could potentially tie:

environmental datasets to cloud services;

modeling software to proprietary hardware;

simulation access to a particular API;

environmental analytics to data-storage services.

The concern is that customers may be forced to purchase several products from the dominant supplier.

13. Interoperability

Interoperability is particularly important because Earth-system modeling ecosystems depend upon cooperation among:

governments;

universities;

private companies;

meteorological organizations;

satellites;

research laboratories;

insurance companies; and

international institutions.

A dominant platform could undermine competition by preventing its system from communicating effectively with competing systems.

Open technical standards can therefore become a competition-enhancing mechanism.

14. Governance as a Competitive Parameter

Traditional competition law normally focuses on:

price;

output;

quality;

innovation.

For Earth-system platforms, governance itself can become a competitive parameter.

Users may choose a platform based on:

transparency;

data portability;

auditability;

model openness;

interoperability;

neutrality;

accountability.

A platform that deliberately reduces these characteristics could potentially weaken competition.

15. Public Procurement and Governance Centralization

Governments may become major purchasers of Earth-system modeling services.

Suppose a government issues a tender requiring:

"The successful bidder must provide an integrated national climate digital twin, including data, computing, modeling and analytics."

If only one incumbent platform can satisfy the specifications, the tender may unintentionally create a monopoly.

Competition concerns may include:

overly restrictive specifications;

proprietary standards;

incumbent advantages;

exclusion of smaller firms;

long-term vendor lock-in;

bundled contracts; and

lack of data portability.

16. Merger Control

Mergers can accelerate governance centralization.

Particularly important transactions may involve combinations between:

cloud providers and climate-model companies;

satellite-data companies and AI companies;

environmental-data providers and insurers;

HPC providers and simulation companies;

climate analytics companies and infrastructure platforms.

Authorities should examine whether the transaction removes an important future competitor.

This is especially important because Earth-system markets may currently be small but strategically important.

17. Killer Acquisitions

A dominant platform might acquire a small company developing:

superior climate algorithms;

advanced environmental AI;

new simulation techniques;

novel satellite analytics;

decentralized modeling infrastructure.

Even where the target has little current revenue, the acquisition could eliminate an important future competitive threat.

This is analogous to concerns surrounding "killer acquisitions" in digital markets.

18. Algorithmic Governance

An ESM platform may eventually use AI to determine:

which models receive computational resources;

which datasets are prioritized;

which predictions are displayed;

which environmental risks are classified as significant;

which users receive access.

This creates a new competition problem:

The algorithm itself may become the mechanism through which market power is exercised.

If competitors cannot understand or challenge the algorithm, governance becomes opaque.

19. Six Important Case Laws

The following cases provide useful doctrinal foundations even though most were decided in traditional markets rather than specifically in Earth-system modeling.

Case 1: United Brands v Commission

United Brands Company and United Brands Continentaal BV v Commission (Case 27/76)

The European Court of Justice examined market definition and dominance in relation to bananas.

Relevance

The case demonstrates that the relevant market may be narrower than an apparently broad technological or economic sector.

For Earth-system platforms, this supports asking whether:

general cloud computing;

environmental cloud computing;

climate simulation;

high-resolution climate modeling;

should be treated as separate markets.

Principle: Market definition must reflect realistic substitutability.

20. Case 2: Commercial Solvents v Commission

Istituto Chemioterapico Italiano S.p.A. and Commercial Solvents Corporation v Commission (Joined Cases 6/73 and 7/73)

The Court addressed a dominant undertaking's refusal to supply an important input to downstream competitors.

Relevance

An Earth-system platform controlling an indispensable:

environmental dataset;

processing interface;

computational resource;

could raise analogous concerns if it withdraws access specifically to exclude downstream competitors.

Principle: A dominant undertaking cannot use control over an important upstream input to eliminate downstream competition in circumstances amounting to abuse.

21. Case 3: Bronner v Mediaprint

Oscar Bronner GmbH & Co. KG v Mediaprint (Case C-7/97)

The Court established strict conditions for applying the essential-facilities/refusal-to-deal doctrine.

Relevance

This is particularly important for Earth-system modeling.

Not every valuable climate dataset should automatically be treated as an essential facility.

A claimant would need to demonstrate, among other things, that access is indispensable and that there is no realistic alternative.

Principle: Competition law does not generally impose universal access obligations merely because an infrastructure is commercially important.

22. Case 4: Microsoft v Commission

Microsoft Corp. v Commission (Case T-201/04)

The European Union General Court upheld important findings concerning Microsoft's refusal to provide interoperability information and the relationship between operating-system dominance and downstream competition.

Relevance

This is one of the most useful precedents for ESM platforms.

A dominant platform controlling an interface or interoperability mechanism could potentially disadvantage competing:

climate applications;

environmental models;

simulation tools;

data-processing services.

Principle: Control over interoperability can become an instrument of exclusion where the legal conditions for abuse are satisfied.

23. Case 5: Google Shopping

Google LLC and Alphabet Inc. v Commission (Case T-612/17)

The General Court considered Google's preferential treatment of its own comparison-shopping service within its search results.

Relevance

The case is highly relevant to self-preferencing.

Imagine an Earth-system platform that:

hosts multiple climate models;

operates its own model; and

systematically ranks its own model above competitors.

The platform could potentially distort competition by controlling the gateway through which users discover competing models.

Principle: Dominance over an important platform interface can create competition concerns where the platform uses that position to favour its own downstream service.

24. Case 6: Bronner and IMS Health

IMS Health GmbH & Co. OHG v NDC Health GmbH & Co. KG (Case C-418/01)

The Court examined access to a commercially important information structure protected by intellectual-property rights.

Relevance

Earth-system platforms may similarly involve proprietary:

datasets;

data structures;

model architectures;

APIs;

technical standards.

The case demonstrates that competition law must balance exclusionary rights against the need to preserve downstream competition.

Principle: Compulsory access to proprietary infrastructure requires exceptional circumstances.

25. Case 7: Slovak Telekom

Slovak Telekom a.s. v Commission and Commission v Slovak Telekom (Joined Cases C-165/19 P and C-166/19 P)

The case concerned exclusionary conduct involving access to telecommunications infrastructure.

Relevance

It provides useful guidance for infrastructure-dependent digital ecosystems.

Earth-system platforms may similarly control infrastructure upon which downstream businesses depend.

The analogy is particularly strong where a vertically integrated provider controls both:

upstream infrastructure; and

downstream services.

Principle: A dominant vertically integrated undertaking can face competition-law scrutiny where its infrastructure strategy forecloses downstream rivals.

26. Case 8: Qualcomm

Qualcomm Inc. v European Commission (Case T-235/18)

The EU General Court examined the use of payments and commercial incentives by a dominant undertaking in the chipset sector.

Relevance

Earth-system platforms might offer:

preferential cloud credits;

discounts;

computational subsidies;

exclusive access;

to customers on condition that they use the platform's own modeling ecosystem.

Such arrangements can raise exclusionary concerns where they foreclose competitors.

Principle: Commercial incentives offered by dominant undertakings may become abusive where they have exclusionary effects.

27. Case 9: Hoffmann-La Roche

Hoffmann-La Roche & Co. AG v Commission (Case 85/76)

The Court established important principles concerning loyalty-inducing practices by dominant undertakings.

Relevance

An ESM platform might create ecosystem loyalty through:

exclusive contracts;

preferential pricing;

proprietary data formats;

API restrictions;

long-term computational commitments.

The competition analysis would focus on whether these practices prevent competitors from competing effectively.

28. Case 10: Google Android

Google LLC v Commission (Case T-604/18)

The case involved Google's practices concerning the Android ecosystem and the relationship between different products and services.

Relevance

It demonstrates how competition concerns can arise across interconnected technological ecosystems rather than within one isolated product.

Earth-system platforms may similarly operate as ecosystems involving:

Cloud + Data + AI + Models + APIs + Applications.

A conduct that appears harmless at one layer may become exclusionary when its effects are assessed across the whole ecosystem.

29. Governance Centralization and Article 102 TFEU

Under Article 102 TFEU, relevant theories may include:

Refusal to supply

Denial of indispensable infrastructure.

Discriminatory access

Different access terms for competitors.

Self-preferencing

Favouring proprietary environmental services.

Tying

Making access to one environmental service conditional upon purchasing another.

Margin squeeze

Setting upstream and downstream prices so competitors cannot compete effectively.

Exclusive dealing

Preventing customers from using competing modeling platforms.

Predatory pricing

Temporarily pricing platform services below sustainable levels to eliminate competitors.

30. Article 101 TFEU and Collective Governance

Governance centralization does not necessarily require a single dominant company.

Several major Earth-system platform providers could coordinate through:

common standards;

data-sharing agreements;

interoperability arrangements;

procurement consortia;

model-validation bodies.

Cooperation can be legitimate and even environmentally beneficial.

However, Article 101 concerns could arise if cooperation becomes a mechanism for:

market allocation;

exclusion;

price fixing;

coordinated refusal to supply;

discriminatory technical standards.

31. Environmental Benefits and Competition Law

A major difficulty is that Earth-system modeling frequently produces public-interest benefits.

For example, cooperation can improve:

climate prediction;

disaster preparedness;

environmental monitoring;

emissions reduction;

scientific research.

Competition authorities therefore should not treat all cooperation as anticompetitive.

The correct approach is to distinguish:

pro-competitive scientific cooperation

from

commercial exclusion disguised as scientific cooperation.

32. Public-Private Governance

An unusual feature of ESM platforms is the possibility of public-private hybrid governance.

A government may:

fund the infrastructure;

provide datasets;

contract private technology companies;

establish technical standards;

rely on private cloud services.

This creates a complicated question:

Who controls the competitive conditions of the ecosystem?

A private company may have formal contractual authority while effectively exercising regulatory influence.

33. Vendor Lock-In

Long-term dependency is one of the largest risks.

A government might invest billions in one platform and later discover that:

datasets cannot easily be exported;

models cannot run elsewhere;

APIs are proprietary;

staff are trained around one system;

historical simulations use proprietary formats.

Switching becomes extremely expensive.

This produces technological path dependence.

34. Data Portability

Data portability can reduce this problem.

Government and research users should ideally be able to:

export datasets;

transfer models;

move computational workloads;

migrate APIs;

retain historical simulation results.

Portability can reduce switching costs and make market entry easier.

35. Open Standards

Open standards can prevent governance centralization.

Examples include standards relating to:

data formats;

APIs;

metadata;

model exchange;

geospatial information;

environmental data interoperability.

Open standards permit multiple providers to compete around a common infrastructure.

36. The Risk of Computational Monopolies

Earth-system modeling increasingly depends upon enormous computational resources.

If only a handful of companies control:

GPUs;

cloud infrastructure;

supercomputers;

specialized accelerators;

they may exercise market power even if the modeling software itself is competitive.

This creates a layered monopoly:

Hardware monopoly → Cloud monopoly → Computing monopoly → Modeling dependency.

Competition authorities therefore need to examine the entire stack.

37. Vertical Foreclosure in the ESM Stack

Consider:

Hardware manufacturer → cloud provider → model platform → environmental application.

If the same corporate group operates all four layers, it could potentially:

discriminate against rival models;

reserve computing capacity for its own products;

impose higher prices on rivals;

restrict technical compatibility;

obtain privileged access to user data.

The resulting problem is vertical foreclosure.

38. AI and Earth-System Modeling

AI substantially increases these concerns.

AI models can assist with:

climate forecasting;

weather prediction;

biodiversity modeling;

emissions forecasting;

environmental risk assessment.

But advanced AI systems may also create new entry barriers because they require:

massive datasets;

specialized chips;

enormous computing capacity;

sophisticated engineering teams.

Therefore, the convergence of AI and ESM can reinforce existing market concentration.

39. Competition Between Models

A healthy ecosystem should permit multiple models to compete on:

accuracy;

speed;

cost;

transparency;

robustness;

geographic coverage;

uncertainty estimation.

If one platform controls the benchmark against which all models are assessed, it may influence competition itself.

This creates a particularly serious form of governance power:

Control over the rules by which competitors are evaluated.

40. Model Validation as a Bottleneck

Suppose a platform controls certification.

Only "approved" models can be used in government procurement.

If certification is:

expensive;

opaque;

discriminatory;

controlled by an incumbent;

then certification can become an artificial entry barrier.

Competition authorities should therefore examine whether technical standards are objectively justified.

41. Environmental Digital Twins

Large-scale Earth digital twins may become especially important.

A digital twin could combine:

climate;

oceans;

agriculture;

infrastructure;

energy;

transportation;

population;

emissions.

If one provider controls the digital twin, government planning may become dependent upon that provider.

This could create a new category of infrastructure:

computationally mediated public infrastructure.

42. The Regulatory-Platform Nexus

The greatest long-term risk is not necessarily conventional monopoly pricing.

The deeper risk is:

Market power → infrastructure dependence → governance dependence → regulatory influence.

Once government institutions depend upon a platform, the platform may gain bargaining power over:

procurement terms;

technical standards;

data-sharing rules;

regulatory implementation.

Competition law must therefore increasingly consider structural dependency.

43. Remedies

Possible competition remedies include:

Structural remedies

divestiture;

separation of infrastructure and applications;

separation of data and downstream services.

Behavioural remedies

non-discriminatory access;

interoperability;

API access;

data portability;

transparent ranking.

Procurement remedies

multi-vendor procurement;

modular tenders;

open technical standards;

migration clauses.

Data remedies

portability;

standardized formats;

access under objective conditions.

Governance remedies

independent oversight;

algorithmic auditing;

transparency obligations;

conflict-of-interest safeguards.

44. Regulatory Sandboxes

Authorities could establish environmental-AI sandboxes allowing competing firms to test:

models;

APIs;

datasets;

interoperability;

digital twins.

This would reduce the possibility that a single incumbent controls the entire innovation pathway.

45. Competition Impact Assessment

Major Earth-system modeling projects could undergo a competition impact assessment before procurement or deployment.

The assessment could examine:

number of potential suppliers;

switching costs;

data portability;

interoperability;

proprietary standards;

exclusivity;

computational dependency;

merger effects;

access to government datasets;

long-term governance consequences.

46. Indian Competition-Law Perspective

In India, the principal framework is the Competition Act, 2002.

Potentially relevant provisions include:

Section 3

Anti-competitive agreements, including arrangements that restrict competition.

Section 4

Abuse of dominant position.

Potential conduct could involve:

denial of market access;

discriminatory conditions;

unfair conditions;

leveraging dominance;

tying;

exclusionary practices.

Sections 5 and 6

Merger and combination control may become important where major technology, cloud, AI, satellite-data and environmental-modeling businesses consolidate.

The Competition Commission of India could therefore eventually encounter ESM questions through:

cloud infrastructure;

AI platforms;

digital markets;

government procurement;

environmental technology;

satellite-data markets.

47. Key Competition-Law Questions

Authorities should ask:

Who owns the critical environmental data?

Who controls computational infrastructure?

Can competitors access the platform?

Can users switch providers?

Are APIs interoperable?

Are technical standards neutral?

Does the platform favour its own models?

Are government contracts excessively exclusive?

Can competitors access equivalent computing resources?

Does the platform control certification?

Are acquisitions eliminating emerging competitors?

Does the platform influence public regulatory decisions?

48. Six Core Legal Principles Emerging From the Case Law

The case law collectively suggests six important principles.

49. Overall Assessment

Earth System Modeling Platforms represent a future category of strategic digital infrastructure.

Their competitive importance arises because they may simultaneously control:

Data + Computing + Models + Algorithms + Interfaces + Standards + Government Access.

The resulting market power may therefore differ from traditional monopoly power.

A platform might charge reasonable prices while still possessing substantial power because competitors cannot realistically reproduce its:

data advantages;

computing ecosystem;

network;

standards;

user base;

government relationships.

Consequently, governance centralization should be treated as a potential competition concern in its own right, particularly when a private platform becomes indispensable to public environmental decision-making.

Conclusion

The competition-law challenge posed by Earth-system modeling platforms is fundamentally structural. The issue is not merely whether one company sells more climate-modeling software than its rivals. It is whether control over the underlying computational ecosystem allows a firm or consortium to determine who participates, what data can be accessed, which models compete, which standards apply and how environmental information reaches governments and markets.

The doctrines developed in United Brands, Commercial Solvents, Bronner, Microsoft, Google Shopping, IMS Health, Slovak Telekom, Qualcomm and Hoffmann-La Roche provide important analytical tools. They can be adapted to assess refusal of access, interoperability restrictions, self-preferencing, vertical foreclosure, exclusivity, tying and ecosystem-based dominance.

The central regulatory objective should therefore be to preserve contestability, interoperability, data portability, model diversity and institutional independence while still permitting the scientific cooperation necessary to address climate change and other Earth-system challenges.

In this emerging field, competition law may ultimately serve not only to protect consumers from higher prices, but also to prevent the emergence of private computational governance structures capable of controlling critical environmental knowledge and infrastructure.