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Platform

Platform Overview

Models

Applications

Coverage Areas

Features & Access

Excel Add-in

Public Analytics

The Climate Risk Navigator for Agriculture gives a quick and up-to-date overview of weather and climate projections for over 40 major crops, for anywhere in the world.&nbsp; This application connects historical weather data, current and near term forecasts, climate projections, and proprietary Gro Climate Indicators such as drought and flood.Types Of Data Available Within The Navigator<ul><li>Historical weather and growing conditions: NDVI, Soil Moisture, GPM aggregated precipitation</li><li>Current and near-term forecasts: GFS temperature and precipitation, Satellite land surface temperature</li><li>Gro Climate projections: Projected data to 2100 for five climate scenarios (such as SSP1-1.9 and SSP5-8.5), including key variables such as temperature and precipitation. Data is sourced from multiple CMIP6-contributing labs and bias-adjusted to improve decision-usefulness. Users are able to view projected point estimates as well as standard deviations.</li><li>Gro Climate Indicators (GCI): GCI - Drought Index, GCI - Weather Variability, GCI - Observed Flood, and more are in development</li></ul>Customers Use This Application to<ul><li>Aggregate weather and climate data for custom selections of countries, states, or districts - combining only regions of interest to create a single decision-useful data series.</li><li>Compare anomalous weather events to previous years, in order to investigate supply and demand reactions.</li><li>Mitigate uncertainty of supply and plan for alternative sourcing locations, by connecting 20 years of historical data to projections out to 2100.</li></ul>Why It MattersThe Climate Risk Navigator for Agriculture allows Gro users to evaluate and compare crop growing conditions anywhere in the world, in real time and on a historical basis.&nbsp;This application can instantly generate crop/location-weighted analyses in a matter of seconds, or be used to compare differences between counties within a region selected. This data can be viewed alongside other Gro data sources such as prices, stocks, and plantings.Related Resources&nbsp;<a href="https://gro-intelligence.com/insights/india-wheat-export-ban-risks-inflaming-food-insecurity-worldwide">India Wheat Export Ban Risks Inflaming Food Insecurity Worldwide</a> Insight<a href="https://gro-intelligence.com/insights/canadian-drought-pushes-canola-to-new-contract-highs">Canadian Drought Pushes Canola to New Contract Highs</a> Insight<a href="https://www.gro-intelligence.com/gro-models/gro-drought-index">Gro Drought Index</a> Display<a href="https://app.gro-intelligence.com/displays/wRL71mOqp">California Vegetable Monitor</a> Display &nbsp;

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Climate Risk Navigator for Agriculture

Gro’s GCIP - Temperature Projections and the GCIP - Precipitation Projections span from 2015 to 2100.&nbsp;These indicators are based on&nbsp; projections from the Coupled Model Inter-comparison Project (CMIP6) generation of climate models for five climate scenarios that have been featured in the IPCC’s <a href="https://gro-intelligence.com/blog/gro-analysis-ipcc-report">Sixth Assessment Report</a>, released in August 2021. These scenarios match the new Shared Socioeconomic Pathways (SSPs) that have been combined with&nbsp; Representative Concentration Pathways (RCPs) to show different possible states of the world based on the possible policy actions we choose in the next few years.Our GCIP - Temperature Projections and the GCIP - Precipitation Projections indicators provide users with district-level projections for two of the most important characteristics of our future climate: temperature and precipitation.&nbsp;By doing this, our indicators facilitate the probabilistic analysis of climate change impacts for any asset or supply chain, and they support long-term strategic planning.&nbsp;&nbsp;Customers use these indicators to<ul><li>Understand the impact that changes in these two key variables might have on future agricultural yields&nbsp;</li><li>Inform long-term planning and decision making related to operations and infrastructure</li><li>Analyze if a business should relocate based on changing climate conditions</li></ul>Why It MattersGro users can use these indicators' long-term projections to determine how future shifts in weather could impact agricultural areas. This information can inform farmers’ planting decisions and help companies determine which assets and sourcing locations may require investments in climate mitigation strategies. These Indicators can also be used to help identify regions that, while unfavorable for growing certain crops today, will become more suitable for growing crops in the future.&nbsp;Related Resources&nbsp;<a href="https://gro-intelligence.com/models/Gro-Climate-Indicator-Weather-Variability" target="_blank" rel="noopener noreferrer">Gro Climate Indicator - Weather Variability&nbsp;</a><a href="https://gro-intelligence.com/models/gro-climate-indicator-observed-flood" target="_blank" rel="noopener noreferrer">Gro Climate Indicator &nbsp;- Observed Flood</a><a href="https://app.gro-intelligence.com/displays/K9p76GARE">Display: Gro Climate Indicator: Precipitation Variation</a>

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Gro Climate Indicator Projection - Temperature and Precipitation Projections

Gro’s Climate Indicator Projection - Heavy Precipitation (GCIP-HP) shows future extreme precipitation using CMIP6 projections for future rainfall.&nbsp;The GCIP-HP represents the 95th percentile (“P95”) of daily precipitation over all wet days; it covers any region worldwide, down to the district level, for any year up to 2095.&nbsp;To produce an accurate estimate of heavy precipitation, Gro corrects for climate model bias by calibrating the GCIP-HP to observed historical records. Climate models often have biases in both the mean and probability distribution of precipitation, meaning that P95 might be too low or too high if not bias-corrected.&nbsp;By combining climate model simulations of historical climate with observations of precipitation from the Global Precipitation Measurement (GPM) satellite (which is also available through Gro), we derive a bias correction factor for P95 which we can then apply to our future climate simulations.Customers use the indicator to<ul><li>Identify geographical areas and physical assets or operations that will likely see an increase or decrease in heavy precipitation at levels that can cause negative impacts</li><li>Project future extreme weather and precipitation events through 2095</li><li>Plan and prepare for climate change effects</li></ul>Why It MattersExtreme precipitation is a climate peril that is likely to change considerably as climate change progresses. Much of the world is expected to experience an increase in the frequency and the intensity of heavy rainfall events due to weather pattern shifts linked to climate change. Heavy rainfall events can have multiple negative impacts, ranging from crop loss to urban flooding to landslides.Related Resources&nbsp;<a href="https://gro-intelligence.com/models/gro-climate-indicator-weather-variability" target="_blank" rel="noopener noreferrer">Gro Climate Indicator - Weather Variability&nbsp;</a><a href="https://gro-intelligence.com/models/gro-climate-indicator-observed-flood" target="_blank" rel="noopener noreferrer">Gro Climate Indicator &nbsp;- Observed Flood</a><a href="https://app.gro-intelligence.com/displays/K9p76GARE">Display: Gro Climate Indicator: Precipitation Variation</a>

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Gro Climate Indicator Projection - Heavy Precipitation

Gro Climate Indicator (GCI) - Observed Flood identifies potential flooding and flooding extent at a granular level anywhere in the world. The indicator makes this possible by comparing the daily extent of surface water with satellite imagery of normal expected surface water conditions.Customers use the indicator to<ul style="list-style-type:disc;"><li>Monitor flooding of any district worldwide</li><li>Determine how much of a country/province/district has been flooded</li><li>Calculate risk of agricultural areas affected by floods</li></ul>Why It MattersBy showing users where flooding has occurred (or might be occurring), our Observed Flood indicator can help decision makers understand how crops might have been affected from a recent flood.Related Resources&nbsp;<a href="https://gro-intelligence.com/models/Gro-Climate-Indicator-Weather-Variability" target="_blank" rel="noopener noreferrer">Gro Climate Indicator - Weather Variability</a>&nbsp;<a href="https://app.gro-intelligence.com/displays/K9p76GARE">Display: Gro Climate Indicator: Precipitation Variation</a><a href="https://app.gro-intelligence.com/displays/WdP34wE95">Display: Gro Climate Indicator: Temperature Variation</a>

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Gro Climate Indicator - Observed Flood

Gro’s Climate Indicator (GCI) - Weather Variability measures the frequency and magnitude of extreme weather events to provide insight into a specific region’s weather variability. Regions with lower variation tend to have more consistent weather patterns, while regions with higher variation tend to experience more extreme weather events. (Our GCI for Weather Variability was previously known as the Climate Variation Index.)Customers use this indicator to<ul style="list-style-type:disc;"><li>Identify regions that have the largest and smallest variations in weather to inform operations and strategic planning</li><li>Analyze how incidence of extreme weather events has changed over time in a given region</li></ul>Why It MattersThe indicator shows how predictable weather variability in a given region is, and the change in frequency and magnitude of extreme weather events in a given region over time. This allows Gro users to determine which regions are experiencing more extreme weather events, possibly due to climate change. This is helpful for designing long-term sustainability strategies that take potential climate impacts into account.Related Resources&nbsp;<a href="https://app.gro-intelligence.com/displays/K9p76GARE">Display: Gro Climate Indicator: Precipitation Variation</a><a href="https://app.gro-intelligence.com/displays/WdP34wE95">Display: Gro Climate Indicator: Temperature Variation</a>

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Gro Climate Indicator - Weather Variability

Gro’s Land Suitability Ranking identifies areas of the globe that are well suited to grow a given crop outdoors without sophisticated irrigation. Gro’s algorithm uses a combination of soil property and climate data to identify the districts that are most similar to the highest yielding region (seed region) in the world and ranks them according to similarity. This allows procurement teams to diversify their supply chains across different regions as well as examine how existing sourcing regions compare with the rankings.<figure class="image"><img src="https://res.cloudinary.com/gro-intelligence/image/upload/v1640032384/new-website/image_cd7f6f0483.png"></figure>Customers use this application to&nbsp;<ul><li>Inform sourcing decisions by finding the most suitable land for a given crop or region</li><li>Identify patterns related to climate change and assess long-term climate risks</li><li>Find alternative sourcing areas for key ingredients/commodities that are grown in concentrated areas or areas at high risk to climate change</li></ul>Why It MattersThis application allows Gro users to find the most well-suited region to grow a given crop and invest in those regions. Conversely, the model can also be used to identify the most well-suited crops to grow in a region. It also enables procurement and sustainability teams to engage in long-term planning.&nbsp;Land suitability can also be applied to long-range sustainability and climate change analysis when combined with the long-range climate scenarios. The model can be used with any crop for which Gro has yield data at the district level.&nbsp;&nbsp;Related Resources<a href="https://gro-intelligence.com/models/supply-location-monitor">Supply Location Monitor</a><a href="https://www.gro-intelligence.com/gro-models/gro-drought-index">Gro Drought Index&nbsp;</a><a href="https://gro-intelligence.com/applications/climate-risk-navigator-for-agriculture" target="_blank" rel="noopener noreferrer">Climate Risk Navigator for Agriculture</a>

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Land Suitability Ranking

The Gro Drought Index (GDI) is the world’s first high resolution global agricultural drought index. It differs from traditional indices in that, beyond precipitation, it factors in several other ecology-driven indicators that closely track the sequence of events leading to drought, giving a more accurate evaluation of the impact of both drought intensity and duration on agriculture. GDI measures drought severity on a scale from “0” (no drought) to “5” (exceptional drought). The index is global, offering data on the continent, country, state, and district level and updates daily.<figure class="image image_resized" style="width:75%;"><img src="https://res.cloudinary.com/gro-intelligence/image/upload/v1633119352/mfcylzlib4sklmt81lnw.png" alt=""></figure>&nbsp;Customers use this index to<ul><li>Monitor drought in key regions for early warning signs of how drought may impact crop production, supplies, prices, and farmer income</li><li>Anticipate potential price-moving events in real time and plan product demand accordingly</li><li>Complement Gro’s Yield Forecast Models ahead of planting to indicate potential planting intentions</li></ul>Why It MattersAgricultural drought impacts crop production, soil degradation, and desertification. It is also an important factor in crop supplies, prices, and farmer income. Detecting drought early allows for advance business planning to mitigate potential negative consequences of unfavorable growing conditions. Drought is also a key risk factor for wildfires, dust storms, and water stress.&nbsp;Related Analytics<a href="https://app.gro-intelligence.com/displays/gR80DOrRe">Gro Drought Index&nbsp;</a><a href="https://app.gro-intelligence.com/displays/eRJpy8GdV">Gro Drought Index for US Corn Belt&nbsp;</a><a href="https://gro-intelligence.com/applications/climate-risk-navigator-for-agriculture">Climate Risk Navigator for Agriculture</a>

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Gro Drought Index

Gro’s Anomaly Detection algorithm provides a mechanism for checking large amounts of data and sending alerts when an anomalous event has occurred.&nbsp;Customers Use This Model To:<ul><li>Analyze data series of important agricultural regions.</li><li>Detect types of anomalies of any series in any region.</li><li>Check a large amount of data and receive an alert whenever a significant anomalous event occurs.</li></ul>Methodology<figure class="image"><img src="https://res.cloudinary.com/gro-intelligence/image/upload/v1635967503/new-website/image_eee448da5e.png"></figure><ul><li>Retrieve all time series data for selected regions</li><li>In the case of daily LST, transform data into 7-day averages</li><li>Check if the most recent data points are greater than two standard deviations from the mean</li><li>Format into a text alert</li></ul>Why It MattersUsers are able to select frameworks for discovering anomalous weather events that could have significant impact on crop production and make better long-term forecasting decisions.&nbsp;Related resources:<a href="https://app.gro-intelligence.com/displays/gR80DOrRe" target="_blank" rel="noopener noreferrer">Gro Drought Index</a><a href="https://app.gro-intelligence.com/displays/eVqe0w0dL" target="_blank" rel="noopener noreferrer">Anomaly Detection -Land Surface Temperature Chart</a>

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Anomaly Detection

Gro’s US Planting Intentions Model allows users to project how much crop will be available in the coming year based on producers’ planting intentions for each of the major crops. The model can also be used to predict demand for agricultural inputs. Model results are available 3 to 4 weeks before the USDA’s Prospective Plantings report is released.<figure class="image image_resized" style="width:75%;"><img src="https://res.cloudinary.com/gro-intelligence/image/upload/v1617656270/fgdav4xgfrp06r18rpgn.png" alt=""></figure>Customers Use the Model to<ul><li>Predict planting intentions for corn, soybeans, cotton, and wheat</li><li>Forecast state and regional seed and crop protection demand</li><li>Understand US production of important global crops</li></ul>Why It MattersFarmers adjust their planting decisions each year based on commodity prices, weather, and crop rotation practices. These planting intentions are important to a range of companies for forecasting regional demand for seed and crop protection and in planning for future seasons. The US is one of the largest agricultural producers globally, and changes in US planting intentions impact crop supply and prices worldwide. Utilizing a variety of current and historical datasets within the Gro Portal, including local new crop cash prices, Gro is able to predict US planting intentions for US corn and soybeans at the state level, cotton at a regional level, and total US spring and durum wheat.Related Analytics&nbsp;<a href="https://www.gro-intelligence.com/gro-models/us-crop-budget-app">&nbsp;</a><a href="https://www.gro-intelligence.com/gro-models/gro-drought-index">Gro Drought Index</a><a href="https://www.gro-intelligence.com/gro-models/us-soy-prevent-plant">US Soy Prevent Plant Model&nbsp;</a>

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US Planting Intentions Model

Gro’s US Soybean Prevent Plant Model, which launches annually at the end of April and runs until the end of June, estimates the number of acres prevented from being planted at the county and national levels in advance of the USDA FSA release. Significant prevent plant area can impact seed sales, input use, and ultimately production. It also drives insurance claims. Even when adverse environmental conditions merely delay planting, crop yields can decline and fewer inputs may be used during the growing season.Gro's US Soybean Prevent Plant Model accurately forecasts the amount of acres prevented from being planted – coming within 99% of final government reporting – up to 6 months in advance.Customers Use the Model to<ul><li>Estimate how many corn and soybean acres in the United States will be prevented from being planted due to excess precipitation or drought conditions</li><li>Track supplies in the US, which can have potential price-moving implications globally</li><li>Forecast demand for agricultural inputs and insurance claims</li><li>Assess the earnings impact for input companies</li></ul>Why It MattersPrevent plant is an insurance contract that nearly all US farmers have. If they are unable due to weather to plant corn or soybeans by a certain date of the year, they can take an insurance pay out and not plant anything in their fields.&nbsp; Farmers therefore need to decide by a certain date, which varies by state, whether to plant or not plant. If there is extreme weather, a large number of farmers will take the payout and must report what they planted and what was prevented from being planted.&nbsp;&nbsp;A decrease in supply for the US market has price moving implications globally. For example, in 2019, the first year the Gro Model launched and accurately forecasted prevent plant acres, the US Midwest experienced record flooding, which had a major impact on prices, planting decisions, and earnings, especially for seed and fertilizer companies.&nbsp;Related Resources&nbsp;<a href="https://www.gro-intelligence.com/gro-models/us-corn-prevent-plant">US Corn Prevent Plant Forecast Model&nbsp;</a><a href="https://info.gro-intelligence.com/2022-performance-report-on-yield-forecast-and-acreage-models" target="_blank" rel="noopener noreferrer">2022 Gro Performance Report</a>

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US Soy Prevent Plant

Gro’s US Corn Prevent Plant Model, which launches annually at the end of April and runs until the end of June, estimates the number of acres prevented from being planted at the county and national levels in advance of the USDA FSA release. Significant prevent plant area can impact seed sales, input use, and ultimately production. It also drives insurance claims. Even when adverse environmental conditions merely delay planting, crop yields can decline and fewer inputs may be used during the growing season.Gro's US Corn Prevent Plant Model accurately forecasts the amount of acres prevented from being planted – coming within 99% of final government reporting – up to 6 months in advance.Customers Use the Model to<ul><li>Estimate how many corn and soybean acres in the United States will be prevented from being planted due to excess precipitation or drought conditions</li><li>Track supplies in the US, which can have potential price-moving implications globally</li><li>Forecast demand for agricultural inputs and insurance claims</li><li>Assess the earnings impact for input companies</li></ul>Why It MattersPrevent plant is an insurance contract that nearly all US farmers have. If they are unable due to weather to plant corn or soybeans by a certain date of the year, they can take an insurance payout and not plant anything in their fields. Farmers therefore need to decide by a certain date, which varies by state, whether to plant or not plant. If there is extreme weather, a large number of farmers will take the payout and must report what they planted and what was prevented from being planted.&nbsp;A decrease in supply for the US market has price-moving implications globally. For example, in 2019, the first year the Gro Model launched and accurately forecasted prevent plant acres, the US Midwest experienced record flooding, which had a major impact on prices, planting decisions, and earnings, especially for seed and fertilizer companies.&nbsp;Related Resources&nbsp;<a href="https://www.gro-intelligence.com/gro-models/us-soy-prevent-plant">US Soy Prevent Plant Model&nbsp;</a><a href="https://info.gro-intelligence.com/2022-performance-report-on-yield-forecast-and-acreage-models" target="_blank" rel="noopener noreferrer">2022 Gro Performance Report</a>

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US Corn Prevent Plant

Gro’s Argentina Soybean Crush Forecast Model helps users as they develop pre-season and in-season plans based on projected supply and demand balance sheets and anticipated exports of soybean products.Argentina, the largest exporter of soybean products in the world, primarily uses its large soybean crop in the domestic crushing industry. Other soybean crush estimates, including the USDA’s, make assumptions about the balance sheet and adjust in-season, but these forecasts update with a considerable lag that can mislead supply and demand estimates. Gro’s Argentina Soybean Crush Forecast Model arrives at its production number quicker because it combines Gro’s yield model, which updates daily, with monthly crush data from Argentina’s Ministry of Agriculture (MAGyP).Customers use this model to<ul><li>Forecast soybeans crush total both ahead of the season and in-season&nbsp;</li><li>Get a breakdown of Argentina’s total soybean use&nbsp;</li><li>Arrive at more accurate futures prices by incorporating soybean crush forecasts into Gro’s Automated Balance Sheet app or into a proprietary supply and demand balance sheet</li></ul>&nbsp;Why this MattersThe crush model forecast gives users the ground truth for forecasting crush availability,&nbsp; which impacts soybean and soybean oil prices globally.&nbsp;MethodologyThis model produces an estimate for annual Argentina soybean crushing before the start of the marketing year and throughout the season incorporating monthly local crush data. The model has been back tested against USDA and MAGyP, &nbsp;the ground truth soybean crush values.&nbsp;Related Resources<a href="https://app.gro-intelligence.com/displays/1Rjz2KwRk">Balance sheet Project - Argentina Soybeans</a><a href="https://gro-intelligence.com/insights/articles/forecast-for-continued-dryness-puts-argentina-soy-production-at-risk">Forecast for Continued Dryness Puts Argentina Soy Production at Risk</a><a href="https://app.gro-intelligence.com/displays/EqZbe77q3">Global Soybean Demand Display</a>

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Argentina Soybean Crush Forecast Model

Gro’s US Soy Area Planted Forecast Model predicts how much the number of soybean planted acres will change between the USDA’s June Acreage report and the final numbers being released. Gro’s early projections of final planted area are reported at the county level. Area planted affects production estimates for the upcoming harvest, which will impact regional and global supply and demand balance sheets.Customers Use the Model to<ul><li>Estimate the change in soy area planted numbers from the USDA’s June acreage report to the final numbers</li><li>Assess crop supplies and prices in local regions by combining with Gro’s yield forecast model</li><li>Track how production is shifting</li></ul>Why It MattersThe US Soy Area Planted Model is important in assessing crop supplies and price. In addition, knowledge of harvested area and yield can show Gro users how production may be shifting. The model can be used to assess the likelihood of USDA revisions. Any changes in crop area in the US, one of the largest agricultural producers globally, will impact global crop supply and prices.MethodologyGro’s model improves upon the widely analyzed USDA Acreage report (June 30) by breaking it down to the county (district) level and continues to fine-tune the data using satellite imagery. The model is able to provide district-level granularity by mathematically dividing up the state level data in the USDA report. The USDA does not update its planted acreage forecast typically until the October WASDE report, after it incorporates a few months of Farm Service Agency data, and final planted acreage is reported in January. Gro’s estimates provide a more accurate reflection of true planted area beginning in mid-July.Related Resources<a href="https://gro-intelligence.com/models/us-crop-budget-app">US Crop Budget App&nbsp;</a><a href="https://gro-intelligence.com/models/futures-spread" target="_blank" rel="noopener noreferrer">Futures Spread App</a><a href="https://gro-intelligence.com/models/us-corn-area-planted-forecast-model" target="_blank" rel="noopener noreferrer">US Corn Area Planted Forecast Model</a>

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US Soy Area Planted Forecast Model

Gro’s US Corn Area-Planted Forecast Model predicts how much the number of corn-planted acres will change between the USDA’s June Acreage report and the final numbers being released. Gro’s early projections of final planted area are reported at the county level. Area planted affects production estimates for the upcoming harvest, which will impact regional and global supply and demand balance sheets.Customers Use the Model to<ul><li>Estimate the change in corn-area-planted numbers from the USDA’s June Acreage report to the final numbers</li><li>Assess crop supplies and prices in local regions by combining with Gro’s US Corn Yield Forecast Model</li><li>Track how production is shifting</li></ul>Why It MattersThe US Corn Area-Planted Model is important in assessing crop supplies and price. In addition, knowledge of harvested area and yield can show Gro users how production may be shifting. The model can be used to assess the likelihood of USDA revisions. Any changes in crop area in the US, one of the largest agricultural producers globally, will impact global crop supply and prices.MethodologyGro’s model improves upon the widely analyzed USDA Acreage report (June 30) by breaking it down to the county (district) level and continues to fine-tune the data using satellite imagery. The model is able to provide district-level granularity by mathematically dividing up the state level data in the USDA report. The USDA does not update its planted acreage forecast typically until the October WASDE report, after it incorporates a few months of Farm Service Agency data, and final planted acreage is reported in January. Gro’s estimates provide a more accurate reflection of true planted area beginning in mid-July.Related Resources&nbsp;<a href="https://www.gro-intelligence.com/gro-models/us-crop-budget-app">US Crop Budget App&nbsp;</a><a href="https://gro-intelligence.com/models/us-planting-intentions">US Planting Intentions&nbsp;</a><a href="https://gro-intelligence.com/insights/new-gro-supply-monitor-app-optimizes-rancher-feed-economics" target="_blank" rel="noopener noreferrer">New Gro Supply Monitor App Optimizes Rancher Feed Economics</a>

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US Corn Area Planted Forecast Model

Gro’s Brazil Soybean Export Forecast Model produces a daily estimate for Brazilian soybean exports before the start of the marketing year and throughout the season.&nbsp; Brazil is the world’s largest soybean producer and exporter, eclipsing the US for this distinction in 2013. Because nearly 70% of Brazil’s crop is exported, Brazil soybean production, exports, and crush can significantly affect global purchasing decisions and trade flows.&nbsp;&nbsp;&nbsp;Our Brazil soybean export forecast model produces a daily export estimate that market participants can use to guide sourcing and planning decisions pre-season, in-season, and at the end of the growing season.&nbsp;The insights generated by Gro’s Brazil Soybean Export Forecast Model can inform agribusiness and sovereign food sourcing planning strategies, as well as shipping companies’ contracting and fleet positioning plans.&nbsp;Customers use this model to<ul><li>Get a baseline pre-season soybean export forecast&nbsp;</li><li>Track how yield forecasts are impacting export projections each day&nbsp;</li><li>Assess the impact of weather and climate events on Brazil’s soybean crop&nbsp;</li><li>Anticipate Brazil’s export capacity and flow to make informed sourcing and shipping decisions&nbsp;</li></ul>Why It MattersBrazil, which produces over 130 million tonnes of soybeans annually, is the largest exporter of soybeans globally. As such, its exports drive trade flows and influence other major exporters’ production and export calculations.Ultimately, our Brazil Soybean Export Forecast Model will be added to an automated Gro Brazil soybean supply and demand balance sheet tool that will provide Gro users with a daily stocks-to-use and ending stocks forecast.&nbsp;Related Resources<a href="https://app.gro-intelligence.com/displays/WdK0k3bqK">Gro Brazil Soybean Export Forecast Model</a> Display <a href="https://app.gro-intelligence.com/displays/6qAxMrgd4">Brazil Soybean Monitor</a> Display <a href="https://gro-intelligence.com/models/futures-spread" target="_blank" rel="noopener noreferrer">Futures Spread App</a>

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Brazil Soybean Export Forecast Model

Gro’s Brazil Soybean Crush Forecast Model provides a pre-season and in season estimate for soybean crush in Brazil, the world’s soybean export leader. Because Brazil is the world’s largest soybean producer and exporter, the processing of its soybeans into meal and soybean oil is closely watched globally.&nbsp;With Gro’s forecast for Brazil’s domestic soybean crush, users can get a snapshot of global soybean crush demand. They can also use our Brazil Soybean Crush Forecast Model to predict soybean ending stocks in Brazil. Supply and demand in Brazil is key to understanding the global balance sheet of soybeans and how that will impact trade flows and price.Customers Use the Model to<ul><li>Monitor Brazil’s soybean crush demand in season</li><li>Get a global picture of soybean crush demand</li><li>Forecast Brazil’s soybean ending stocks</li><li>Anticipate Brazil’s soybean available export capacity and flow to make better sourcing and shipping decisions</li></ul>Why It MattersBrazil is the global leader in soybean exports, and soybean crush is a major use for its crop. Having access to a Brazil soybean crush estimate can help users position themselves ahead of the USDA’s monthly supply and demand data releases (WASDE), and it can help users arrive at a more finely tuned soybean ending stocks estimate.Related Resources<a href="https://gro-intelligence.com/models/us-crop-budget-app" target="_blank" rel="noopener noreferrer">US Crop Budget App</a> <a href="https://gro-intelligence.com/models/futures-spread" target="_blank" rel="noopener noreferrer">Futures Spread Application</a>

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Brazil Soybean Crush Forecast Model

Gro’s Yield Forecast Models use a suite of machine-learning models to estimate in-season yields at the district, province, and/or national levels on a daily basis. Gro’s Brazil Corn Yield Forecast Model is updated daily, providing in-season yields for corn at the district, province, and national levels throughout the growing season.Customers Use the Model to<ul><li>Track corn production in the world’s third-largest corn-producing country</li><li>Monitor crop production, the most significant part of the balance sheet, by tracking its most variable component, which is in-season yield</li><li>Gauge crop availability and crop prices</li><li>Understand how weather impacts yields in microclimates</li><li>Inform other models focused on damage caused by pests and diseases</li></ul>Why It MattersBrazil’s second crop corn area, or safrinha, has grown significantly on the back of soybean expansion. Currently, Brazil is the world’s third-largest corn producer and the second-largest exporter of corn in the world. Crucially, the country’s main export window overlaps with the US harvest, pushing the main US export window into Q1. Corn production is concentrated in four of Brazil’s 26 states: Mato Grosso, Minas Gerais, Goias, and Parana. When combined with our other Corn Yield Forecast Models, for China, the United States, and Argentina, Gro is able to forecast more than 70% of global corn production in a given year, providing users with a highly accurate, real-time window into global corn supply.MethodologyModeling corn yield in Brazil presents particular challenges, primarily because there are two corn-growing seasons per year. Further, the breakdown of the two annual crops has changed: the second-season crop has become more dominant, as soybeans have taken priority over the first corn crop during the summer season. In addition, significant differences in weather, soil conditions, and technology adoption around the country results in high spatial variation of crop yields. Gro’s Brazil Corn Yield Forecast Model uses the following variables:<ul><li>Latitude and longitude</li><li>Gro Crop Cover</li><li>Yield, area and production history in Brazil</li><li>Eight-day normalized difference vegetation index (NDVI)</li><li>Land surface temperature</li><li>Rainfall</li><li>Weather forecasts of air temperature and precipitation</li><li>Evapotranspiration difference from 10-yr median (2003-2013)</li><li>Drought Severity and Coverage Index</li><li>Soil characteristics</li><li>Latitude and longitude</li><li>30-meter resolution cropland masks</li></ul>Related Resources<a href="https://app.gro-intelligence.com/displays/wRL7Npgqp">Gro Brazil Corn Yield Forecast Model Inputs</a><a href="https://gro-intelligence.com/gro-models/us-corn-yield-model">US Corn Yield Forecast Model</a><a href="https://gro-intelligence.com/gro-models/argentina-corn-yield-model">Argentina Corn Yield Forecast Model</a><a href="https://gro-intelligence.com/gro-models/china-corn-yield-models">China Corn Yield Forecast Model</a>

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Brazil Corn Yield Forecast Model

Gro’s Yield Forecast Models use a suite of machine-learning models to estimate in-season yields at the district, province, and/or national levels on a daily basis. Gro’s US Corn Yield Forecast Model gives county-level and national-level forecasts. The model uses spatially explicit weather, vegetation health, and soil data, to monitor environmental and crop conditions during the growing season and continuously forecast final yield.&nbsp;Customers Use the Model to<ul><li>Gauge crop availability and crop prices</li><li>Understand how weather impacts yields in microclimates</li><li>Inform other models focused on damage caused by pests and diseases</li><li>Monitor crop production, the most significant part of the balance sheet, by tracking its most variable component, which is in-season yield</li><li>Make early-season forecasts of end-of-season yield in the US and across the Corn Belt, which produces 80%-85% of national corn</li></ul>Why It MattersCorn is a particularly valuable crop to model, given its importance to global food supply and economic trade. The US is the largest producer and consumer of corn, accounting for a third of the world’s corn production. The area planted affects estimates of upcoming harvest sizes, which in turn impact regional and global supply and demand balance sheets. But corn yields can vary substantially across years, with forecast production changing frequently within a season due to rapid shifts in weather.MethodologyUsing USDA data, we applied our agronomic expertise to select the best variables on a county-by-county basis. Then we tested those variables on the 918 most relevant counties, instead of just on one national number. After removing the linear trend growth, we performed a “leave one year out” analysis, for example fitting a model to “forecast” 2011 using every year between 2000 and 2016 except 2011. Some variables selected by our experts include:<ul><li>Normalized difference vegetation index (NDVI)</li><li>Land surface temperature (LST)</li><li>Rainfall data (GPM)</li><li>Crop condition surveys</li><li>Crop calendars</li><li>Acreage planted and harvested</li><li>Soil surveys (gSSURGO)</li><li>Cropland data (CDL)</li></ul>Related Resources<a href="https://gro-intelligence.com/insights/articles/us-corn-price-correction-may-be-short-lived-gro-sees-ending-stocks-drop" target="_blank" rel="noopener noreferrer">US Corn Price Correction May Be Short-Lived, Gro Sees Ending-Stocks Drop</a><a href="https://www.gro-intelligence.com/insights/articles/us-corn-is-king-now-but-production-costs-threaten-its-reign" target="_blank" rel="noopener noreferrer">US Corn Is King Now, but Production Costs Threaten Its Reign</a><a href="https://app.gro-intelligence.com/displays/V9NBDbJ9b" target="_blank" rel="noopener noreferrer">US Corn Prevent Plant Monitor Display</a>

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US Corn Yield Forecast Model

Gro’s Yield Forecast Models use a suite of machine-learning models to estimate in-season yields at the district, province, and/or national levels on a daily basis. Gro’s US Hard Red Wheat Yield Forecast Model updates daily to give national yield forecasts for hard red winter wheat, as well as winter wheat yield forecasts at the county level. The model offers in-season, near-real-time yield analysis, operating across three states—Kansas, Oklahoma, and Texas—which together account for about 60% of US total production of hard red winter wheat.<figure class="image image_resized" style="width:75%;"><img src="https://res.cloudinary.com/gro-intelligence/image/upload/v1638554047/new-website/US_Hard_Red_Winter_Wheat_Yield_Forecast_Model1_d9f6fbb390.png"></figure>&nbsp;Customers Use the Model to<ul><li>Monitor crop production, the most significant part of the balance sheet, by tracking its most variable component, which is in-season yield</li><li>Gauge crop availability and crop prices</li><li>Forecast hard red winter wheat yield in areas that account for more than half of US production</li><li>Understand how weather impacts yields in microclimates</li><li>Inform other models focused on damage caused by pests and diseases</li></ul>Why it MattersThe US is the third-biggest national exporter of wheat, after Russia and Canada. Despite a decline in US wheat acreage in recent years, the crop continues to occupy a significant portion of US farmland. Wheat grown across the country shows considerable variations in planting calendar, protein content, and market uses; specialized models that track different varieties are valuable for monitoring the downstream impact of changes in wheat yield. Hard red winter wheat (HRW), which is high in protein and suitable for baking, accounts for over a third of total US wheat production — nearly 18 million tonnes in 2020. About half of the crop is exported, which means that hard red winter wheat yields also have ramifications on global trade dynamics.MethodologyBecause the USDA doesn’t provide county-level yield specifically for HRW, we trained our model on overall winter wheat yield in regions that are almost exclusively HRW. We tested a number of geospatial inputs for our model, of which normalized difference vegetation index (NDVI) and evapotranspiration (ET) performed the best during the backtest. Besides these geospatial inputs, weekly winter wheat crop conditions from the USDA (at the state level) also helped improve the model’s performance.Related Resources<a href="https://www.gro-intelligence.com/insights/articles/extreme-freeze-likely-damaging-us-winter-wheat-crop">Extreme Freeze Likely Damaging US Winter Wheat Crop</a><a href="https://gro-intelligence.com/models/us-winter-wheat-crop-cover" target="_blank" rel="noopener noreferrer">US Winter Wheat Crop Cover&nbsp;</a><a href="https://gro-intelligence.com/insights/articles/gro-data-reveals-new-problems-for-us-wheat-production">Gro Data Reveals New Problems for US Wheat Production</a><a href="https://gro-intelligence.com/insights/articles/quantifying-how-much-us-winter-wheat-could-be-abandoned">Quantifying How Much US Winter Wheat Could Be Abandoned</a>

US Hard Red Winter Wheat Yield Forecast Model

Models

Environmental: Weather & Climate

Climate Risk Navigator for Agriculture

Gro Climate Indicator Projection - Temperature and Precipitation Projections

Gro Climate Indicator Projection - Heavy Precipitation

Gro Climate Indicator - Observed Flood

Gro Climate Indicator - Weather Variability

Land Suitability Ranking

Gro Drought Index

Anomaly Detection

Supply

US Planting Intentions Model

US Soy Prevent Plant

US Corn Prevent Plant

Yield Forecast

Argentina Soybean Crush Forecast Model

US Soy Area Planted Forecast Model

US Corn Area Planted Forecast Model

Brazil Soybean Export Forecast Model

Brazil Soybean Crush Forecast Model

Brazil Corn Yield Forecast Model

US Corn Yield Forecast Model

US Hard Red Winter Wheat Yield Forecast Model

Argentina Soybean Yield Forecast Model

India Wheat Yield Forecast Model

Ukraine Winter Wheat Yield Forecast Model

Brazil Soybean Yield Forecast Model

US Soybean Yield Forecast Model

China Corn Yield Forecast Model

Argentina Corn Yield Forecast Model

Canada Spring Wheat Yield Forecast Model

China Wheat Yield Forecast Model

Russia Winter Wheat Yield Forecast Model

Australian Wheat Yield Forecast Model

Crop Cover

US Winter Wheat Crop Cover

Canada Spring Wheat Crop Cover

Australian Wheat Crop Cover

Brazil Soybean Crop Cover

US Corn Crop Cover

US Soybean Crop Cover

Argentina Soybean Crop Cover

India Wheat Crop Cover

Demand

China Pork Demand Forecast Model

Price

Supply Location Monitor

US Farmer Profitability Application

Custom Price Index Application

Stocks-to-Use vs. Price Framework

Gro's Global Balance Sheet

Broiler Chicken Margin Monitor

US Ag Price Index

China Ag Price Index

US Retail and Wholesale Volatility Adjusted Price Index

US Retail and Wholesale Price Volatility Indices

India Food Price Inflation Index and Retail Price Volatility Indices

China Corn Balance Sheet

India Retail Price Volatility Indices

Pest & Disease

Brazil Asian Soybean Rust

Locust Vegetation Impact Model