Dendrology

Where data meets insight → charting a clearer future

Dendrology Weather Model

Hyper-Accurate Weather Prediction Model v3.2.1

What could be A Dendrology future — illustrative, not yet delivered.

A working mock of the model Dendrology intends to run — live data arrives in a later phase.

Weather Prediction Intelligence

Enterprise-grade numerical weather prediction system featuring 4D-Var data assimilation, ensemble Kalman filtering, and machine learning post-processing. Delivers unprecedented accuracy through real-time integration of 11,000+ surface stations, 800+ radiosondes, satellite constellations, and advanced physics parameterizations.

Parameter Specification
Spatial Resolution 0.25° - 0.03125° (25km - 3km)
Forecast Horizon 384 hours (16 days)
Update Cycle 6-hourly with 15-min temporal resolution
Ensemble Members 51 (Operational) / 100 (Research)

Model Overview

98.7%
24hr Temperature Accuracy
94.2%
72hr Precipitation Skill
1.34°C
Temperature RMSE
0.94
Ensemble Spread-Skill
11,000+
Surface Stations
700K+
Daily Aircraft Reports

Interactive Forecasting Interface

Model Control v3.2.1

Operational

Current Ensemble Statistics

Spread: 0.94
Reliability: 0.91
Sharpness: 0.88
Resolution: 0.85

Model Diagnostics

Analysis Tools

Data Quality Monitor

Satellite Coverage 98.2%
Surface Observations 96.7%
Aircraft Reports 87.3%
Radiosonde Data 94.1%

Verification Options

Performance Metrics

RMSE (24h)
1.34°C
Bias
-0.12°C
Correlation
0.967
Skill Score
0.92

Alert Thresholds

3.0
15
5

Active Alerts

Aircraft observation coverage below 90% in CONUS region
Ensemble spread optimization completed for 06Z cycle

Notification Settings

Real-time Performance

Model Status Operational
Last Update 00:15 UTC
Processing Time 47 min
Data Latency 8 min
Lat: 40.71°N, Lon: 74.01°W
2024-01-15 12:00 UTC
Model: v3.2.1 | Res: 2.5km | Members: 51
2024-01-15 12:00 UTC +0 hours
Now +3d +7d +14d

Weather Layers

1000m
Temperature (°C)
-20
40
Precipitation (mm/hr)
0
50+
Wind Speed (m/s)
Light (0-5)
Moderate (5-15)
Strong (15+)

Ensemble Prediction System

Ensemble Spread Analysis

Probabilistic Forecasts

85%
Rain > 1mm
23%
Rain > 10mm
5%
Rain > 25mm
92%
Temp 15-25°C

Model Diagnostics & Performance

Bias Analysis

-0.3°C
↓ Improving

Skill Scores

RMSE: 1.8°C
MAE: 1.2°C
Correlation: 0.94

Data Sources

Satellite
Radiosondes
Surface Stations
Aircraft

Model Documentation

Model Architecture

Numerical Weather Prediction Core
Component Description Methods
Dynamical Core Non-hydrostatic compressible atmosphere model with advanced physics parameterizations
  • Semi-Lagrangian advection scheme
  • Hybrid sigma-pressure vertical coordinates
  • Spectral transforms for global coupling
Machine Learning Components
Component Description Methods
Deep Neural Networks Multi-scale convolutional networks for pattern recognition and bias correction
  • ResNet architecture for temperature prediction
  • U-Net for precipitation downscaling
  • Transformer models for time series forecasting