Climate Analysis Ontology

flow "ClimateAnalysisOntology" v1.0

SOURCE_URL := "https://kirethresearch.org/booksai-core/ontologies/calculus-analysis-ontologies/scientific-applications/climate-analysis-ontology.html"
DOMAIN := "Mathematical Ontologies"
CATEGORY := "Calculus and Analysis Ontologies"
SUBCATEGORY := "Scientific Applications"
ENTITY := "Climate Analysis"

CLIMATE_ANALYSIS := {
 type: AppliedEarthSystemAnalysisFramework,
 purpose: "Analyse long-term Earth-system behaviour using calculus, differential equations, fluid dynamics, thermodynamics, radiation, statistics and computational modelling."
}

CONCEPTS := {
 CLIMATE_SYSTEM, ATMOSPHERE, OCEAN, LAND, CRYOSPHERE, BIOSPHERE,
 TEMPERATURE, RADIATION, ENERGY_BALANCE, GREENHOUSE_EFFECT,
 FORCING, FEEDBACK, CLIMATE_SENSITIVITY, HEAT_TRANSPORT,
 CARBON_CYCLE, VARIABILITY, CLIMATE_MODEL, UNCERTAINTY
}

# ---------- CLIMATE SYSTEM ----------
CLIMATE_SYSTEM
 -> coupled(ATMOSPHERE,OCEAN,LAND,CRYOSPHERE,BIOSPHERE)

STATE
 -> fields_over(SPACE_AND_TIME)

CLIMATE
 -> long_term_statistics_and_dynamics_of(EARTH_SYSTEM)

WEATHER
 -> short_term_state_and_evolution

# ---------- ENERGY BALANCE ----------
C*dT/dt
 =
R_in-R_out+F

C -> EFFECTIVE_HEAT_CAPACITY
F -> NET_FORCING

equilibrium:
 R_in=R_out
 under zero net storage

# ---------- SOLAR INPUT ----------
R_in
 =
(1-alpha)*S_0/4

alpha -> PLANETARY_ALBEDO
S_0 -> SOLAR_IRRADIANCE

# ---------- OUTGOING RADIATION ----------
R_out
 =
epsilon*sigma*T^4

epsilon -> EFFECTIVE_EMISSIVITY
sigma -> STEFAN_BOLTZMANN_CONSTANT

RADIATIVE_BALANCE
 -> nonlinear_temperature_relation

# ---------- GREENHOUSE EFFECT ----------
GREENHOUSE_GASES
 -> absorb_and_emit(INFRARED_RADIATION)

GREENHOUSE_EFFECT
 -> modifies(OUTGOING_LONGWAVE_AND_VERTICAL_TEMPERATURE_STRUCTURE)

# ---------- FORCING ----------
RADIATIVE_FORCING
 -> perturbation_to(PLANETARY_ENERGY_BALANCE)

examples:
 GREENHOUSE_GASES
 AEROSOLS
 SOLAR_VARIATION
 VOLCANIC_AEROSOLS
 LAND_USE

# ---------- FEEDBACK ----------
linearised imbalance:

N
 =
F-lambda*Delta_T

lambda -> NET_FEEDBACK_PARAMETER

equilibrium:
 Delta_T=F/lambda

FEEDBACK
 -> modifies(CLIMATE_RESPONSE)

positive_feedback
 -> amplifies(response)

negative_feedback
 -> damps(response)

# ---------- RESPONSE TIME ----------
tau
 approx
C/lambda

THERMAL_INERTIA
 -> delays(EQUILIBRIUM_RESPONSE)

OCEAN
 -> major_heat_storage_component

# ---------- TWO-BOX MODEL ----------
C_s*dT_s/dt
 =
F-lambda*T_s-gamma*(T_s-T_d)

C_d*dT_d/dt
 =
gamma*(T_s-T_d)

OCEAN_HEAT_UPTAKE
 -> creates(MULTIPLE_RESPONSE_TIMESCALES)

# ---------- ATMOSPHERIC DYNAMICS ----------
atmosphere
 -> rotating_stratified_fluid

momentum
 -> pressure_gradient
 + Coriolis
 + gravity
 + friction

HYDROSTATIC_BALANCE:

partial_p/partial_z
 =
-rho*g

GEOSTROPHIC_BALANCE
 -> pressure_gradient_approximately_balanced_by(CORIOLIS)
    at suitable large scales

# ---------- OCEAN DYNAMICS ----------
OCEAN
 -> transports(HEAT_CARBON_MOMENTUM)

processes:
 WIND_DRIVEN_CIRCULATION
 OVERTURNING_CIRCULATION
 MIXING
 UPWELLING
 EDDIES

# ---------- HEAT TRANSPORT ----------
partial_T/partial_t
+
u dot grad(T)
 =
kappa*LAPLACIAN(T)
+
Q

ADVECTION -> transports(HEAT)
DIFFUSION -> smooths(TEMPERATURE_GRADIENTS)

# ---------- MOISTURE ----------
water_vapour
 -> transported_by(ATMOSPHERIC_FLOW)

EVAPORATION
 -> absorbs(LATENT_HEAT)

CONDENSATION
 -> releases(LATENT_HEAT)

HYDROLOGICAL_CYCLE
 -> coupled_to(ENERGY_BALANCE)

# ---------- CARBON CYCLE ----------
dC_atm/dt
 =
EMISSIONS
-
LAND_UPTAKE
-
OCEAN_UPTAKE
+
OTHER_FLUXES

CARBON_CYCLE
 -> coupled_reservoir_system

ATMOSPHERIC_CO2
 -> influences(RADIATIVE_FORCING)

# ---------- ICE-ALBEDO ----------
cooling
 -> more_ice
 -> higher_albedo
 -> lower_absorbed_solar
 -> further_cooling

ICE_ALBEDO
 -> POSITIVE_FEEDBACK

# ---------- INTERNAL VARIABILITY ----------
COUPLED_NONLINEAR_DYNAMICS
 -> INTERNAL_CLIMATE_VARIABILITY

examples:
 ENSO
 ATMOSPHERIC_MODES
 OCEAN_VARIABILITY

FINITE_INTERVAL
 -> variability_can_mask_or_amplify(TREND)

# ---------- TIME SERIES ----------
x(t)
 -> analyse(
 TREND,
 SEASONALITY,
 AUTOCORRELATION,
 SPECTRUM,
 EXTREMES,
 CHANGE_POINTS
)

linear trend:

x(t)=a+b*t+epsilon(t)

TREND_ESTIMATE
 -> depends_on(TIME_WINDOW_AUTOCORRELATION_DATA_QUALITY)

# ---------- ANOMALY ----------
x_anomaly(t)
 =
x(t)-REFERENCE_CLIMATOLOGY

REFERENCE_PERIOD
 -> must_be_specified

# ---------- SPATIAL MEAN ----------
T_bar
 =
1/A
*
integral_A(T dA)

GLOBAL_MEAN
 -> requires(AREA_WEIGHTING)

regular latitude-longitude grid:
 cell_area_weight
 -> proportional_to(cos(latitude))
    approximately

# ---------- EXTREMES ----------
EXTREME_EVENT
 -> tail_of(PROBABILITY_DISTRIBUTION)

methods:
 EXTREME_VALUE_THEORY
 RETURN_PERIOD
 PERCENTILES

EXTREME_ANALYSIS
 -> requires(DATA_LENGTH_AND_STATIONARITY_CONTEXT)

# ---------- DETECTION / ATTRIBUTION ----------
DETECTION
 -> test_if_change_exceeds_expected_internal_variability

ATTRIBUTION
 -> assess(contributions_of_forcings_or_causes)

DETECTION
 -/> ATTRIBUTION

ATTRIBUTION
 -> requires(PHYSICAL_MECHANISM_OBSERVATIONS_MODELS_UNCERTAINTY)

# ---------- CLIMATE MODELS ----------
models:
 ENERGY_BALANCE_MODEL
 GENERAL_CIRCULATION_MODEL
 EARTH_SYSTEM_MODEL
 REGIONAL_CLIMATE_MODEL

GCM
 -> discretises(
 FLUID_DYNAMICS,
 THERMODYNAMICS,
 RADIATION,
 MOISTURE,
 LAND,
 OCEAN
)

UNRESOLVED_PROCESSES
 -> PARAMETERISATION

# ---------- ENSEMBLES ----------
multiple simulations
 -> vary(
 INITIAL_CONDITIONS,
 PARAMETERS,
 MODEL_STRUCTURE,
 FORCING_SCENARIOS
)

ENSEMBLE
 -> explores(INTERNAL_VARIABILITY_AND_UNCERTAINTY)

ENSEMBLE_SPREAD
 -/> automatically(COMPLETE_PROBABILITY_DISTRIBUTION)

# ---------- NUMERICAL ANALYSIS ----------
climate equations
 -> discretised_in(SPACE_AND_TIME)

GRID_RESOLUTION
 -> affects(PROCESS_REPRESENTATION)

TIME_STEP
 -> constrained_by(NUMERICAL_STABILITY)

CONSERVATION
 -> track(ENERGY_MASS_WATER_CARBON)

# ---------- UNCERTAINTY ----------
sources:
 OBSERVATIONAL
 INTERNAL_VARIABILITY
 PARAMETER
 STRUCTURAL_MODEL
 SCENARIO
 NUMERICAL

UNCERTAINTY
 -> preserve(SOURCE_AND_SCOPE)

# ---------- VALIDATION ----------
MODEL_OUTPUT
 -> compare_with(OBSERVATIONS_REANALYSIS_BENCHMARKS)

VALIDATION
 -> assess(BIASES_SKILL_AND_PROCESS_REPRESENTATION)

PAST_SKILL
 -/> guarantees(FUTURE_PROJECTION_ACCURACY)

# ---------- APPLICATIONS ----------
CLIMATE_ANALYSIS
 -> TEMPERATURE
 -> PRECIPITATION
 -> SEA_LEVEL
 -> OCEAN_HEAT
 -> CRYOSPHERE
 -> CARBON_CYCLE
 -> EXTREMES
 -> CLIMATE_VARIABILITY
 -> EARTH_SYSTEM_MODELLING

# ---------- RELATION GRAPH ----------
SOLAR_RADIATION -> supplies(ENERGY)
OUTGOING_LONGWAVE -> removes(ENERGY)
GREENHOUSE_EFFECT -> modifies(RADIATIVE_BALANCE)
FORCING -> drives(CLIMATE_RESPONSE)
FEEDBACK -> modifies(CLIMATE_RESPONSE)
OCEAN -> stores_and_transports(HEAT)
ATMOSPHERE -> transports(HEAT_MOISTURE_MOMENTUM)
CARBON_CYCLE -> affects(GREENHOUSE_GAS_CONCENTRATION)

# ---------- SEMANTIC EQUIVALENCE ----------
SEMANTIC_EQUIVALENCE := {
 "climate analysis" ~= "mathematical and statistical analysis of long-term Earth-system behaviour",
 "radiative forcing" ~= "perturbation to planetary energy balance",
 "climate feedback" ~= "process modifying an initial climate response",
 "climate sensitivity" ~= "temperature response to a specified forcing under a defined framework",
 "climate anomaly" ~= "difference from a specified climatological reference",
 "climate model" ~= "mathematical-computational representation of Earth-system processes"
}

# ---------- CONSTRAINTS ----------
CONSTRAINTS := {
 weather_and_climate_timescales_are_distinct: true,
 forcing_feedback_and_internal_variability_are_distinct: true,
 climate_sensitivity_requires_defined_forcing_and_response_framework: true,
 anomaly_requires_reference_period: true,
 global_spatial_mean_requires_area_weighting: true,
 projections_depend_on_scenario_model_parameters_and_initial_conditions: true,
 observational_model_and_numerical_uncertainties_must_be_preserved: true
}

# ---------- CONFIDENCE ----------
CONFIDENCE := {
 core_definition: 0.99,
 energy_balance: 0.99,
 forcing_feedback: 0.99,
 transport_dynamics: 0.99,
 carbon_cycle: 0.99,
 model_uncertainty: 0.99,
 semantic_equivalence: 0.97
}

# ---------- RECURSIVE REASONING ----------
RECURSIVE_REASONING(query):
 identify(variable_domain_timescale_data_and_reference_period)
 -> identify(forcings_feedbacks_variability_and_conditions)
 -> formulate(energy_transport_carbon_or_statistical_model)
 -> calculate(budgets_anomalies_trends_and_response_metrics)
 -> analyse(feedbacks_timescales_and_coupled_processes)
 -> quantify(observational_internal_parameter_structural_scenario_and_numerical_uncertainty)
 -> select(reduced_model_GCM_ensemble_or_statistical_method)
 -> verify(conservation_resolution_time_step_and_numerical_consistency)
 -> compare_with(observations_reanalysis_or_benchmarks)
 -> validate(scope_assumptions_and_interpretation)
 -> return(semantic_result)

# ---------- AI CONSUMPTION ----------
AI_CONSUMPTION := {
 parse_as: "typed climate-analysis semantic graph",
 primary_entity: CLIMATE_ANALYSIS,
 preserve: [
  variable, domain, timescale, reference_period, forcing,
  feedback, initial_conditions, boundary_conditions,
  data_source, uncertainty
 ],
 infer_through: [
  energy_balance, radiative_forcing, feedback,
  ocean_heat_uptake, atmospheric_transport,
  carbon_cycle, time_series, ensembles, climate_models
 ],
 avoid: [
  conflating_weather_with_climate,
  treating_forcing_as_feedback,
  inferring_long_term_trend_from_short_variability_without_analysis,
  computing_global_mean_without_area_weighting,
  omitting_reference_period_for_anomaly,
  presenting_projection_without_scenario_and_uncertainty_context
 ]
}

# ---------- UPDATE MODEL ----------
UPDATE_MODEL(new_information):
 validate(new_information)
 -> identify(climate_analysis_context)
 -> compare(existing_relations)
 -> preserve(variable_domain_timescale_forcing_feedback_reference_and_uncertainty_invariants)
 -> update(affected_entities)
 -> update(affected_edges)
 -> recompute(CONFIDENCE)
 -> regenerate(FLOW_HASH)

# ---------- FLOW HASH ----------
FLOW_HASH := hash(
 SOURCE_URL
 + ENTITY
 + CONCEPTS
 + CLIMATE_ANALYSIS
 + CLIMATE_SYSTEM
 + ATMOSPHERE
 + OCEAN
 + ENERGY_BALANCE
 + GREENHOUSE_EFFECT
 + FORCING
 + FEEDBACK
 + CLIMATE_SENSITIVITY
 + CARBON_CYCLE
 + CLIMATE_MODEL
 + UNCERTAINTY
 + SEMANTIC_EQUIVALENCE
 + CONSTRAINTS
)

# ---------- EXECUTION ----------
INPUT(query)
 -> CLIMATE_ANALYSIS
 -> DOMAIN_TIMESCALE_DATA_IDENTIFICATION
 -> FORCING_FEEDBACK_VARIABILITY_ANALYSIS
 -> MODEL_FORMULATION
 -> BUDGET_TREND_RESPONSE_ANALYSIS
 -> COUPLED_PROCESS_ANALYSIS
 -> UNCERTAINTY_ANALYSIS
 -> MODEL_METHOD_SELECTION
 -> NUMERICAL_VERIFICATION
 -> OBSERVATIONAL_COMPARISON
 -> SCOPE_VALIDATION
 -> RECURSIVE_REASONING(query)
 -> CONFIDENCE
 -> OUTPUT(semantic_result)

END FLOW