Leverage high-signal indicators across agriculture, climate, and the economy to make consistent trading and investment decisions amidst market volatility and global unpredictability.

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Gro’s daily-updating models such as the Gro Drought Index lead market-moving events up to 4 months in advance. Designed by our team of analysts, climate scientists, and data scientists, these models monitor crop conditions daily to forecast supply-side shocks throughout the growing season. Talk to our team to learn more.

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A suite of machine-learning models that cover 80% of global production for corn, soy, and wheat.

For example, the Gro Drought Index, which measures drought severity for every district on earth.

Data such as temperature and precipitation, key indicators of crop conditions and production.

Example signals for quantitative analysis

All 2.9 million unique Gro data series are accessed directly through our API. 

Gro's 50+ subject matter experts across climate, ag, and economics are available 24/7.

The methodology behind Gro's insights are fully transparent — this is not a “black box."

Key features

Additional Resources

Gro Intelligence has over 2 million unique, proprietary data series that address a range of questions across crop yield and production, supply and demand, growing conditions, and climate scenarios. Gro's data series are built by our team of 50+ domain experts and scaled through artificial intelligence, generating predictive models and real-time applications. Our products provide accurate forecasts and holistic views into the most pressing challenges across climate, agriculture, and the economy.&nbsp;In this report, we focus on the performance of our Global Yield Forecast Models across corn, soy, and wheat, as well as our US Planting Intentions Model and US Prevent Plant Models for corn, soy, wheat, and cotton.&nbsp;You will learn how:&nbsp;<ul><li>Historically, for the past seven years, Gro’s US Corn Yield Forecast Model has been on average within 98.3% of the USDA final January report by September. Our US Soybean Yield Forecast Model has been on average within 99% of the USDA’s final number by September for the last four years.</li><li>In critical global regions, where the current marketplace does not have many machine learning-based predictive models, such as Ukraine, Brazil, and China, Gro’s 2022 Global Yield Forecast Models were on average 95% accurate up to 10 months ahead of final government reporting.</li><li>Gro’s suite of machine-learning models provide an unprecedented combination of accuracy, global coverage, granularity down to the district level, and daily in-season updates to enable our customers to move ahead of the market.</li></ul>Download the 2022 performance report <a href="https://info.gro-intelligence.com/2022-performance-report-on-yield-forecast-and-acreage-models?utm_campaign=End%20of%20the%20Year%20Report%20-%20January%202023&amp;utm_medium=email&amp;_hsmi=2&amp;_hsenc=p2ANqtz--DAawbx4JnPmIhs6GrNfist1fGwSINeh_jnpFQ9_1aaJrTOxCIMEY1Xq-DyHJPXbhZ9TUpn5frwnku07Tb0UXCk7b3NiU9gn6sw5XtheL7Ena6_aw&amp;utm_content=2&amp;utm_source=hs_email" target="_blank" rel="noopener noreferrer">here</a>.

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2022 Performance Report: Gro Yield Forecast Models and Acreage Models

In this report, we will talk about how to use growing and climate conditions in a systematic way to better anticipate impact on final yield throughout the growing season—from planting to harvest.&nbsp;<a href="https://info.gro-intelligence.com/incorporating-climate-into-agricultural-forecasting" target="_blank" rel="noopener noreferrer">Download the report here.</a>

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Incorporating Climate Into Agricultural Forecasting

As global&nbsp;<a href="https://www.gro-intelligence.com/insights/extreme-heat-threatens-crop-prospects-around-the-world">temperatures reach historic extremes</a>, land surface temperature (LST) becomes an especially critical input when predicting the impact of heat stress on crop planting, development, production, and yield. In July, to complicate matters further, NASA’s two satellites that house MODIS sensors – which detect and measure land surface temperature among many other datasets – are experiencing an outage due to a data lapse from its Adaptive Processing System where data from several NASA satellites is processed for users.In 2022, after witnessing a series of other satellite data lapses, Gro’s research and development teams created a Gro LST measure to safeguard against outages like the one we’re experiencing now, ensuring Gro’s measurement of land surface temperature is not disrupted by a single-source outage.“Gro LST” is a generative AI model that incorporates observations from multiple LST and air temperature sources, shares information across them, and delivers a consistent and complete representation of a synthetic LST time-series. The result is an aggregated LST metric that can approximate a valid LST observation every day for all target geographies regardless of data availability from underlying LST and air temperature sources.&nbsp;While datasets ingested from the NASA MODIS sensors remain an input to Gro LST, they are one of many, ensuring Gro LST can continue to provide the same highly accurate LST values to our models.&nbsp;<figure class="image"><img src="https://res.cloudinary.com/gro-intelligence/image/upload/v1690819466/new-website/Temperature_Availability_FINAL_3ff788f51a.png"></figure>Today, Gro LST is a key input to&nbsp;<a href="https://www.gro-intelligence.com/platform/models" target="_blank" rel="noopener noreferrer">Gro’s yield forecast models</a>, preserving model performance during data disruptions or outages from other temperature sources.&nbsp;While these types of outages are relatively short-lived, they can be unpredictable and data lags can last for several weeks.&nbsp;Geospatial data disruptions or delays are caused by a number of factors including faulty satellites, government shutdowns,&nbsp;lags in availability, and even cloud cover.&nbsp;Given the current MODIS outage, the contingencies built into Gro LST have proved to be beneficial and we anticipate that there will be no practical impact to the quality of Gro’s yield forecasts.To learn more about Gro models and methodology,&nbsp;<a href="https://www.gro-intelligence.com/contact">contact a member of our team here</a>.&nbsp;

Quantitative Funds

Get ahead of market volatility with Gro's high-signal indicators

Anticipate price movements up to 4 months sooner

Example signals for quantitative analysis

Global Yield Forecast Models

Proprietary Weather Indicators

Satellite-Derived Environmental Data

Key features

Delivered through an API

Analyst expertise

Transparency

Additional Resources

2022 Performance Report: Gro Yield Forecast Models and Acreage Models

Incorporating Climate Into Agricultural Forecasting

Gro’s Temperature Generative AI Model: Building Resiliency to Data Disruption