Every renewable business decision rests on a weather claim: the yield report on a resource dataset, the trading book on a production forecast, the storage bid on a price-and-load view. The data-and-forecasting layer has quietly become its own software category — APIs and platforms feeding everything downstream. This guide compares the resource-data and forecasting providers on identical criteria, from bankable satellite archives to open public datasets.
Bankable resource archives: Solargis — the data family yield reports cite; public list pricing.
Full-atmosphere weather API: Meteomatics — one API for every parameter a portfolio touches.
Demand & market forecasting: Amperon — AI load and renewable forecasts for trading desks.
Measurement-anchored forecasts: Vaisala — sensing heritage applied to energy prediction.
Free public baseline: NREL NSRDB & Open-Meteo/ERA5.
Scope: weather, resource, and production-forecasting data services for renewable energy — historical archives for bankability, live and forecast feeds for operations and trading, and the free public datasets beneath them. Plant design tools consuming this data are covered in our solar and wind comparisons; price benchmarks in the PPA guide. Six entries, identical criteria; order follows the data lifecycle, not rank.
Criteria: data types and horizons, validation pedigree, delivery model (API, platform, files), licensing, geographic coverage, and the main tradeoff. Pricing spans public lists, free tiers, and enterprise quotes — each labeled as such (checked September 19, 2026).
At a Glance
| Platform | Pricing | Best For | Link |
|---|---|---|---|
| Solcast (DNV) | Free evaluation tiers; paid plans quote-based | Solar forecasting & live data via API | solcast.com → |
| Solargis | Public price list — Prospect from €2,400/yr; Evaluate €12,000/yr | Bankable solar resource data | solargis.com → |
| Meteomatics | Quote-based (free basic API account) | One weather API for all parameters | meteomatics.com → |
| Amperon | Enterprise subscription (quote-based) | Load & renewable forecasts for markets | amperon.co → |
| Vaisala | Quote-based | Measurement-anchored energy forecasting | vaisala.com → |
| NSRDB & Open-Meteo/ERA5 | Free | Public baseline data & research | nsrdb.nrel.gov → |
Pricing checked September 19, 2026. Most platforms in this category sell quote-based enterprise plans; where we cite figures they come from vendor pages or published third-party comparisons and are order-of-magnitude indications, not offers. Billing basis (per user, per MW, per site) varies by vendor — confirm current terms directly before budgeting.
The Platforms in Detail
Solcast (DNV)
The solar API standard
Best for: product and operations teams who want irradiance and PV power data flowing into their own systems, not another dashboard.
| Data types | Live estimated actuals, forecasts, historical time series and TMY for irradiance and PV power |
| Method | Satellite-derived irradiance updated at high frequency, tuned for PV use cases |
| Delivery | Developer-grade API; per-site and portfolio products |
| Licensing | Free evaluation tiers (limited requests; unmetered locations for testing); commercial plans quote-based. Checked September 19, 2026 |
| Pedigree | Acquired by DNV — certifier-grade governance behind an API-first product |
| Main tradeoff | Solar-first; wind products exist but the center of gravity is PV |
- API-first design means forecast data lands where it earns money — inside SCADA, trading, and monitoring systems — rather than in another browser tab.
- Free evaluation access with real data lets engineering teams validate accuracy on their own sites before procurement begins.
- DNV ownership matters commercially: data feeding a dispute or a lender question carries an assurance brand counterparties recognize.
Solargis
The bankability archive
Best for: developers and investors whose resource numbers must survive lenders, IEs, and a decade of scrutiny.
| Data types | Long-horizon satellite solar archives, TMY, meteo layers; simulation via Evaluate |
| Method | Physically-based satellite modeling with published validation record |
| Delivery | Apps (Prospect, Evaluate), data downloads, and API |
| Licensing | Public price list — Prospect €2,400–4,800/yr; Evaluate €12,000/yr with unlimited TMY simulations on 60 early-stage projects. Checked September 19, 2026 |
| Pedigree | A default citation in bankable yield studies worldwide |
| Main tradeoff | Solar resource depth, not a general weather or markets platform |
- When the dataset’s name appears in the yield report, diligence gets shorter — Solargis is one of the few names that consistently does.
- Public, genuinely mid-market pricing for Prospect makes bankable-family data accessible at screening stage, not just at financing.
- Validation transparency — published accuracy by region — is exactly the evidence an IE asks for, offered before they ask.
Meteomatics
The everything API
Best for: teams consolidating weather dependencies — solar, wind, hydro, load drivers, extremes — behind one contract and one syntax.
| Data types | 1,800+ parameters: irradiance, wind fields at hub heights, precipitation, temperature, marine, air quality |
| Method | Model blending with proprietary downscaling; optional own-fleet data assimilation |
| Delivery | A single well-documented API; free basic account for evaluation |
| Licensing | Quote-based packages by industry and volume. Checked September 19, 2026 |
| Pedigree | A cross-industry weather-API leader with a strong energy practice |
| Main tradeoff | Breadth over specialist depth — pure-solar accuracy races are Solcast/Solargis territory |
- One API for the whole portfolio — PV, wind, hydro inflows, demand drivers — collapses a zoo of vendor integrations into a single dependency.
- Hub-height wind parameters without running your own NWP stack serve wind operators that sit below the cost line of bespoke meteorology.
- Uniform syntax across parameters is a real engineering economy: one client library, every weather question.
Amperon
The market forecaster
Best for: trading desks, retailers, and asset owners whose exposure is measured in dollars per MWh, not watts per square meter.
| Data types | AI-driven load forecasts, renewable production forecasts, market analytics |
| Method | Machine learning on meter, market, and weather data; strong ERCOT heritage, expanding coverage |
| Delivery | Platform and API; forecasts also distributed via the Yes Energy ecosystem |
| Licensing | Enterprise subscription; quote-based. Checked September 19, 2026 |
| Pedigree | A recognized name in demand forecasting for volatile markets |
| Main tradeoff | Markets-and-load focus — it consumes weather rather than being your weather archive |
- Built where forecasting errors cost the most — scarcity-priced markets like ERCOT — which disciplines models in ways mild climates never would.
- Load and renewables in one view matches how desks actually take risk: net position, not generation alone.
- Yes Energy distribution slots forecasts into the market-data stack traders already run — adoption without integration projects.
Vaisala
The measurement house
Best for: operators and developers who want forecasting anchored to sensing rigor — and hardware-to-data accountability in one vendor.
| Data types | Weather observations and sensors, renewable forecasting services, atmospheric intelligence |
| Method | A century of measurement science; energy forecasting built on observation-grade inputs (3TIER heritage) |
| Delivery | Services, data feeds, and instrumentation |
| Licensing | Quote-based. Checked September 19, 2026 |
| Pedigree | The instrumentation standard across meteorology, aviation, and energy |
| Main tradeoff | An institution, not a startup API — developer ergonomics are not the pitch |
- Owning the chain from sensor to forecast closes the accountability gap that pure-data vendors leave open when accuracy disputes arise.
- Wind-energy forecasting heritage (3TIER lineage) predates the current API generation — institutional depth in exactly the hard cases.
- For operators already fielding Vaisala instrumentation, extending into forecasting keeps calibration and vendor management coherent.
NREL NSRDB & Open-Meteo/ERA5
The free baseline
Best for: everyone — as the screening layer, the model input, and the check every commercial claim should face.
| Data types | NSRDB satellite solar archives (Americas & beyond); ERA5 global reanalysis; Open-Meteo’s free forecast API |
| Method | Public-science datasets with fully documented methodologies |
| Delivery | Free downloads and APIs |
| Licensing | Free; attribution norms apply |
| Pedigree | The datasets the research literature — and many commercial models — are built on |
| Main tradeoff | Screening and research grade — bankable projects graduate to validated commercial archives |
- The correct starting point everywhere: portfolio screening on NSRDB/ERA5 costs nothing and calibrates expectations before any contract.
- A permanent honesty check — when a vendor’s numbers diverge wildly from public baselines, the burden of proof is theirs.
- Open-Meteo’s free forecast API is quietly sufficient for internal tools and prototypes that would never justify enterprise feeds.
Accuracy Claims, and How to Actually Read Them
Every provider advertises accuracy; almost none of the numbers are comparable. Validation periods differ, reference stations differ, error metrics differ — an RMSE quoted against one network in one climate says little about your site. The honest tell is not the headline number but the disclosure posture: published validation by region, named reference data, and documented methodology changes. Solargis’s public validation record and the public datasets’ full transparency set the standard the rest of the category should be held to.
The practical implication: run your own trial. Most providers — Solcast’s free tiers, Meteomatics’ basic account, the public baselines — allow a zero-cost shadow period where their data is scored against your own meters. Sites with a year of pyranometer or production data can settle in weeks what marketing pages argue forever.
One Stack, Three Time Horizons
The category resolves cleanly along time. Backward: long archives (Solargis, NSRDB, ERA5) establish what the resource is — the bankability question. Sideways: live estimated actuals (Solcast-class) tell operations what should be happening now — the underperformance-detection question our asset-management guide picks up. Forward: forecasts from minutes to days (Solcast, Meteomatics, Amperon, Vaisala) price risk — the trading and dispatch question.
Mature organizations stop shopping for one vendor and start architecting the stack: public data as the base layer, one bankable archive for finance, one operational feed for the fleet, one market forecaster for the desk — with overlap kept deliberately for cross-validation. The line item that looks like duplication is usually the cheapest error-detection system the business owns.
Kurums Match: Which One Fits You?
Pick the statement that sounds most like your situation.
We’re financing projects and need resource numbers lenders accept.
A validated commercial archive is non-negotiable — Solargis-family data is the default citation, with public pricing that no longer reserves it for financing-stage budgets. Keep NSRDB/ERA5 as your internal cross-check.
We operate fleets and need to know when plants underperform.
Live estimated actuals are the tool — Solcast-class feeds against your SCADA separate cloudy from broken. This is the data layer your asset-management platform (see that guide) is only as good as.
We trade power or manage merchant exposure.
Amperon-class load-and-renewables forecasting in market context, with Meteomatics or Solcast feeding weather inputs. Accuracy in scarcity hours — not average days — is the procurement criterion; test exactly those.
We’re building products and want weather data as infrastructure.
Start free on Open-Meteo/NSRDB for prototypes; graduate to Meteomatics for parameter breadth or Solcast for solar specialization when revenue justifies contracts. Design the abstraction so the provider is swappable — this market keeps improving.
Frequently Asked Questions
Satellite data or ground measurement — which do we need?
Both, sequenced. Satellite archives give instant history everywhere and carry screening and early finance; ground campaigns reduce uncertainty for final investment decisions and calibrate the satellite record. The blend — site-adapted satellite data — is the bankable standard.
Are free datasets like NSRDB and ERA5 good enough to build on?
For screening, research, and internal tooling — absolutely. For bankable finance and operational settlement, validated commercial archives and feeds earn their fees through documented accuracy, support, and the credibility counterparties extend them.
How is this category different from the design tools that use the data?
These providers answer what the atmosphere delivers; design tools (PVsyst, windPRO — see our comparisons) turn that into plant-level energy. The design tool inherits the data’s errors, which is why data choice deserves its own procurement rather than riding along as a default.
Do wind projects use the same providers?
Partially. Meteomatics and Vaisala serve wind directly, and reanalysis underpins wind resource work everywhere — but wind’s specialist modeling stack (WAsP, windPRO and peers) is its own world, covered in our wind resource software guide.
Related Comparisons & Guides
- Wind resource assessment software compared
- Best solar design software compared
- Renewable asset management software compared
- PPA price benchmark platforms compared
- Microgrid design software compared
Last updated: September 19, 2026 · Reviewed by the Kurums Startup editorial team.
Disclosure: Kurums currently has no affiliate, sponsorship, or partnership relationship with any product compared on this page. If that changes, this page will say so here and affected links will carry sponsored attributes.
Part of the Kurums Renewable Energy hub — country strategies, permitting, incentives, financing, and tools across nine markets.
Discover more from Kurums | Business Intelligence
Subscribe to get the latest posts sent to your email.