Last updated: 21st January 2026
 

Executive summary

The Demeter Almond Season Index (DASI) is a weather-derived index that tracks growing conditions across California’s almond-producing regions. The index provides a standardised, continuously updated benchmark that allows market participants to compare seasonal conditions both against historical averages and across different crop years.

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DASI synthesises the agronomic variables most important for almond crop development into a single composite score. It is designed to measure growing conditions rather than predict yields, although there is a natural correlation between growing conditions and yields. The index is constructed bottom-up from individual growing locations and aggregated by area weighting to produce regional and statewide figures.

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A DASI value of 100 indicates conditions in line with the long-term historical average. Values above 100 indicate more favourable conditions; values below 100 indicate less favourable conditions. The index typically fluctuates in a range between 60 and 140.

 

Design principles

DASI was designed around three core principles:

1. Observable and universal. The index is derived from observable meteorological data with near-universal spatial coverage. This ensures that DASI can be calculated consistently across all growing regions and compared meaningfully across time. The index does not incorporate survey data, anecdotal reports, or proprietary management information.

2. Continuously available. DASI is calculated from streaming hourly data and updates daily. This provides market participants with a real-time view of how conditions are evolving, rather than periodic snapshots at fixed points in the season.

3. Spatially explicit. The index is constructed from the ground up, anchored in the explicit locations of almond orchards. This allows DASI to be calculated at any geographic granularity, from individual assets to irrigation districts, counties or the entire state.

 

Conceptual framework

Phenological structure

Almond trees progress through distinct phenological stages during the growing season, and the agronomic factors that matter most for crop development differ at each stage. DASI reflects this biological reality by dividing the season into five phases and tracking stage-appropriate metrics within each.

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The present methodology uses fixed date ranges to define each stage, but may transition to dynamic stage definitions in future versions of the index based on observable chill and heat accumulation patterns.

 

Agronomic variables

DASI incorporates the weather-derived variables that scientific literature and industry expertise identify as most influential for almond crop development. Below is a non-exhaustive list:

• Winter chill accumulation. Almond trees require a period of cold temperatures during dormancy to ensure uniform bud break and successful bloom. DASI tracks chill accumulation using established agronomic models and compares it against varietal requirements.

• Bloom conditions. The bloom period is critical for pollination success. Multiple factors affect outcomes during this window, including temperature ranges that influence bee activity, precipitation that can interfere with pollination and promote fungal disease, and wind conditions.

• Frost events. Freezing temperatures during bloom can cause permanent damage to flowers and developing fruitlets. DASI treats frost differently from other variables due to its potential for catastrophic and irreversible impact on the season.

• Heat accumulation. Thermal time accumulation during the fruit development period drives kernel fill and maturation. DASI tracks both the total heat accumulation and the pattern of that accumulation, as the timing of heat exposure affects outcomes.

• Solar radiation. Light availability during fruit development affects photosynthetic activity and carbohydrate allocation to developing kernels. DASI similarly tracks both total accumulation and the pattern of that accumulation for solar radiation.

• Heat stress events. Extreme high temperatures can damage developing fruit and reduce kernel quality, acting as a counterweight to the general benefit of warm conditions.

• Pre-harvest conditions. During hull split and the period leading to harvest, dry conditions and low humidity reduce disease pressure and support crop quality. Rain or high humidity during this period can promote hull rot and aflatoxin development.

 

Index construction

Spatial aggregation

DASI is constructed bottom-up from individual grid cells that correspond to weather data resolution. Each cell containing bearing almond acreage receives an index score based on the conditions observed at that location. The statewide DASI is then calculated as the area-weighted average of all individual cell scores, where area weighting reflects the proportion of total bearing almond acreage contained in each cell.

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This approach ensures that the headline index reflects conditions weighted by actual production footprint. Regions with greater almond concentration contribute proportionally more to the aggregate index than regions with sparse coverage.

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The same methodology allows DASI to be calculated at any level of geographic aggregation. Subscribers can access the index for individual counties, irrigation districts, groundwater sustainability agencies, or custom footprints corresponding to specific asset portfolios or sourcing regions.

 

Statistical approach

Individual agronomic metrics are transformed into standardised scores by comparing current-season values against historical distributions for the same location and time of year. This statistical transformation ensures that all metrics are expressed on a comparable scale and that the index captures deviation from normal conditions rather than raw values.

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The historical baseline used for this comparison spans a multi-year period sufficient to capture typical inter-annual variability in California’s climate. The baseline is held constant to ensure that DASI values remain comparable across different crop years.

 

Weighting and combination

Standardised metric scores are combined using a proprietary weighting methodology that reflects the relative importance of each factor for crop outcomes. Weights were developed through a combination of agronomic research review, consultation with industry experts, and historical calibration against observed yield variability.

The weighting methodology incorporates several key features:

• Stage-appropriate metrics. Each phenological stage has its own set of relevant metrics with stage-specific weights. Metrics that matter during bloom, for example, differ from those that matter during fruit development.

• Progressive accrual. As the season progresses, each stage’s contribution to the overall index accrues proportionally to elapsed time. Early in the season, only the conditions experienced so far contribute to the index; by season’s end, all stages contribute according to their relative importance.

• Multiplicative stress factors. Certain catastrophic events, such as severe frost during bloom, are treated as multiplicative rather than additive factors. Such events impose a permanent penalty on the index for the remainder of the season, reflecting the biological reality that some damage cannot be recovered regardless of how favourable subsequent conditions may be.

 

Data sources

Meteorological data

DASI draws on reanalysis meteorological data from intergovernmental scientific organisations. Reanalysis data combines historical observations from weather stations, satellites, and other sources with atmospheric modelling to produce spatially complete, temporally consistent datasets at hourly resolution.

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This approach offers several advantages over station-based observations alone. Reanalysis data provides complete spatial coverage without gaps and enables consistent historical comparison across multiple decades.

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The primary meteorological variables used in DASI construction include temperature (hourly), precipitation, solar radiation, relative humidity, and wind speed. Derived metrics such as chill accumulation and growing degree days are calculated from these primary inputs using established agronomic formulas.

 

Crop spatial data

Area weighting for index aggregation relies on mapping of almond bearing acreage across California. This mapping integrates data from government bodies, satellite imagery analysis and other sources to identify the location and extent of almond production. The acreage data distinguishes between bearing and non-bearing orchards, as only bearing acreage contributes to near-term production outcomes. Young orchards that have not yet reached bearing age are excluded from the area weighting calculation.

 

Interpretation and use

What DASI measures

DASI measures growing conditions as experienced by the almond crop from the beginning of the season through the date of publication. It encodes the cumulative effect of weather factors on crop development potential.

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A DASI of 100 indicates that conditions have been in line with historical averages when taken together. A higher number indicates more favourable conditions; a lower number indicates less favourable conditions. The index is positively correlated with yield outcomes, and this correlation strengthens when multiple years of DASI are considered together, reflecting the cumulative impact of growing conditions on permanent tree crops.

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Importantly, similar DASI values at the same point in different seasons do not necessarily indicate identical conditions. One year might have experienced a poor winter offset by excellent bloom conditions; another might have had the reverse. The index captures the net effect of all factors according to their assigned importance.

 

What DASI does not measure

DASI is a conditions index, not a yield forecast. It does not incorporate several factors that may significantly affect production outcomes:

• Water availability. Irrigation water supply is a critical determinant of California almond yields. DASI does not incorporate information on surface water allocations, groundwater availability, or orchard-level irrigation decisions.

• Orchard age and productivity. The age profile of bearing acreage affects yield potential. Young orchards have lower yields per acre than mature orchards; very old orchards may be in decline. DASI uses flat area weighting and does not adjust for productivity differences.

• Management factors. Grower decisions on nutrition, pest management, pruning and other cultural practices affect outcomes but are not observable in meteorological data.

• Varietal composition. Different almond varieties have different requirements and sensitivities. DASI does not distinguish between varieties in its area weighting.

These limitations are by design. DASI focuses specifically on the component of crop outcomes attributable to weather conditions, providing a clean signal that can be combined with other information sources in more comprehensive analytical frameworks.

 

Comparison with other information sources

DASI is designed to complement rather than replace other information sources used by market participants. Official yield estimates from government agencies, for example, employ survey methodologies and incorporate information beyond weather conditions. These estimates serve different purposes and are released at different times in the season.

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DASI’s value lies in its continuous availability, its derivation from universal and observable data, and its standardised framework for comparing conditions across time and space. It provides a common reference point for market participants and a transparent input to more complex analytical models.

 

Interpretation and use

Governance and updates

DASI is maintained by Demeter’s index team in consultation with agronomic advisors. The methodology undergoes periodic review to ensure it reflects current scientific understanding and remains well-calibrated against observed outcomes.

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Any material changes to the methodology will be disclosed in advance of implementation. Historical index values may be restated following methodology changes to maintain comparability of the time series.

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The inaugural DASI season (2025/26, the conditions of which will be reflected in the 2026/27 crop marketing year) is designated as a calibration period. Feedback from users and comparison with emerging season outcomes will inform refinements to the methodology before the index enters its standard operational phase.

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Further information

For questions about DASI methodology, subscription options, or integration into other products and workflows, please contact the Demeter index team at sales@demeterdata.ag.​

The headline DASI is published free of charge every other Monday at 4am PST/12pm GMT and is available on Demeter’s website and via email.​

Demeter platform subscribers can access daily updates, regional breakdowns, detailed commentary and custom footprints within the Indices & Monitoring area of the platform.