Application of Numerical WeatherPrediction Models forDrought Monitoring

Gregor GregoričJožef Roškar

Environmental Agency of Slovenia

Contents

1. Introduction

2. Numerical Weather Prediction Models - NWP

3. Application of NWP for Draught Monitoring

4. Verification of Products using Decadal Bulletins

Introduction

Basic condition for any drought management is good knowledge

of drought state

Drought monitoring

(Hydrological cycle,

state of Vegetation)

In-situ measurement

Remote sensing

Indices Indicators

How to get space information?Horizontal interpolation

Remote sensing

Numerical Weather Prediction Models

Numerical Weather Prediction Models - NWP

Simulated/

Predicted

Athmospheric

Variables/Fields

Initial and

Boundary

Conditions

(data archive)

Integration

Numerical resolving of

mathematical equations

describing development of

athmospheric variables in time

Air Pressure

Wind

Temperature

Humidity

Cloudiness

Precipitation

Evaporation

Soil Moisture

Etc.

Real continous space is by the model distributed into equidistant discrete grid

points

Distance between grid points - space resolution defines the smallest structures seenby a NWP:

• Low resolution (~200 km) – simulation of basic structures (planetary waves, big frontal systems) – used for climate modeling and studies of globalmechanisems;

• Medium resolution (50 - 10 km) – simulation of sinoptic and mesoscale systems– used for general weather forecast;

• High resolution (< 10 km) – simulation of local systems (wind, fog, tunderstorms, etc.)

Regardless the resolution, there are

• Global models covering entire globe and

• Limited Area Models simulating weather over choosed smaller area

Numerical Weather Prediction Models - NWP

Weather Observing

System

Weather Observing

System

Data Analysis

Data Asimilation

Initialization

Data Analysis

Data Asimilation

Initialization

Integration

Atmospheric Physics

Surface Physics

Surface Processes

Numerical Methods

Simulated FieldsSimulated Fields

Postprocessing

Vizualization

Postprocessing

Vizualization

Data Collecting

over

Observing Network

Numerical ModelData and Model

Results Presentation

Numerical Weather Prediction Models - NWP

NumericalNumericalNumericalNumerical WeatherWeatherWeatherWeather PredictionPredictionPredictionPrediction ModelsModelsModelsModels ---- NWPNWPNWPNWP• To run a LAM, aa LAM, aa LAM, aa LAM, accessccessccessccess to global archives of weather patterns to global archives of weather patterns to global archives of weather patterns to global archives of weather patterns is is is is neededneededneededneeded• Data in regular grid, internally Data in regular grid, internally Data in regular grid, internally Data in regular grid, internally consistentconsistentconsistentconsistent, , , , withoutwithoutwithoutwithout errorserrorserrorserrors (+)(+)(+)(+)• Not Not Not Not directlydirectlydirectlydirectly relatedrelatedrelatedrelated to to to to actualactualactualactual situationsituationsituationsituation ““““on on on on groundgroundgroundground”””” ((((----))))

Very important over montainous areas

Relief presentation depends on horizontal resolution

Example: slope and precipitation:

Wind

Numerical Weather Prediction Models - NWP

This is why majority of NWP models underestimate precipitation

(Non)Predictability

• Physical Laws– Co-existence of various scales– Interaction of all variables– Exchange of energy among various

scalesChaos

NumericalNumericalNumericalNumerical WeatherWeatherWeatherWeather PredictionPredictionPredictionPrediction ModelsModelsModelsModels ---- NWPNWPNWPNWP

NumericalNumericalNumericalNumerical WeatherWeatherWeatherWeather PredictionPredictionPredictionPrediction ModelsModelsModelsModels ---- NWPNWPNWPNWP

Lorentz butterfly

NumericalNumericalNumericalNumerical WeatherWeatherWeatherWeather PredictionPredictionPredictionPrediction ModelsModelsModelsModels ---- NWPNWPNWPNWP

(Non)Predictability• Physical Laws

– Co-existence of various scales– Interaction of all variables– Exchange of energy among various

scales• Discretization of continous space• Limited computing power• Incomplete knowledge of initial state

NumericalNumericalNumericalNumerical WeatherWeatherWeatherWeather PredictionPredictionPredictionPrediction ModelsModelsModelsModels ---- NWPNWPNWPNWP

UncertaintyUncertaintyUncertaintyUncertaintyTaking into account (Non)Predictability, we have to consider that by themodel simulated parameters and fields are not directly related to actual

parameters, in particular to the situation “on ground”.

HowHowHowHow to to to to reducereducereducereduce uncertaintyuncertaintyuncertaintyuncertainty andandandand useuseuseuse thethethethe NWP NWP NWP NWP productsproductsproductsproducts forforforfor droughtdroughtdroughtdroughtmonitoringmonitoringmonitoringmonitoring????to choose the model and setup it in the way that the output best fits theobservations (might be difficult for precipitation!);

to compute model climatology for some drought related variables using

historical reanalyzes and to develop a tool for drought monitoring like

METEOALARM.

Limited Area Model

Main Idea:

•Take data from global archive

•Choose area and grid points

•Re-simulate weather patterns fromglobal model to obtain more details on a regional scale

NumericalNumericalNumericalNumerical WeatherWeatherWeatherWeather PredictionPredictionPredictionPrediction ModelsModelsModelsModels ---- NWPNWPNWPNWP

Application of NWP for droughtmonitoring

LimitedArea

NMM (NCEP)Non-Hydrostatic

Meso-scaleModel

• Area: 461 x 289 x 92 = 12.257.068 points

(133.229 points “on ground”)

• Top Level: 1 hPa (~ 60 km)

• Horizontal resolution: ~8.5 km

• Time Step: 30 sec.• Integration Time: 36 h starting at 12 UTC to get

simulation for the entire next day

Application of NWP for droughtmonitoring

Application of NWP for droughtmonitoring

OUTPUT:

Simulated and averaged variables (air and soil) – daily aggregates 1989-2008

precip daily sum (00-24h), mmevaporation (and transpiration) daily sum (00-24h), mmpotential evaporation (and transpiration) daily sum (00-24h), mmliquid soil moisture volumetric fraction 0-10cm (24h)liquid soil moisture volumetric fraction 10-40cm (24h)liquid soil moisture volumetric fraction 40-100cm (24h)liquid soil moisture volumetric fraction 100-200cm (24h)total soil moisture volumetric fraction 0-10cm (24h)total soil moisture volumetric fraction 10-40cm (24h)total soil moisture volumetric fraction 40-100cm (24h)total soil moisture volumetric fraction 100-200cm (24h)total soil moisture content (kg/m2) in 0-200cm layer (24h)geopotential height on 850hPa (12h), mtemperature on 850hPa (12h), Kdaily average 10m wind, m/sdaily average 10m wind gusts, m/sdaily min. temperature, Kdaily max. temperature, Kdaily min. relative humidity, %daily max. relative humidity, %

Application of NWP for droughtmonitoring

DROUGHT RELATED VARIABLES

Soil moisture?

DROUGHT RELATED TIME SCALE

Not daily! Decade?

DROUGHT RELATED INTERPRETATION

Not absolute values, deviation from normals

Application of NWP for droughtmonitoring

GOAL:

To re-computereanalyses dataover SE Europe

in dense grid

to obtain“climatology”

for droughtsituationsinterpretation

ECMWF ERA – Interim

1989 - 2008

Model Integration

Area (SE Europe)

Limited Area Model

NNM (NCEP)

Application of NWP for droughtmonitoring

CLIMATOLOGY:

AccumulatedWater Balanceover 70 days

Mean for theperiod 21 May –29 July, dataperiod 1989 -2008

Application of NWP for droughtmonitoring

POSSIBLE PRODUCT:

AccumulatedWater Balanceover 70 days

Anomaly

Application of NWP for droughtmonitoring

POSSIBLE PRODUCT:

10 days SoilMoisture Index -

Anomaly

Application of NWP for droughtmonitoring

POSSIBLE PRODUCT:

10 days MeanTemperature -

Anomaly

How to verify theproducts:

The best waywould becomparison within-situ data

Your help is urgently needed – cooperation all over the region

Verification of Products using DecadalBulletins

Verification of Products using DecadalBulletins

Ten days Bulletins based on the NWP products and verifyed with your helpmight be useful.

Shall we prepare the metodology during the coming 2010 season and put

the bulletins to the internet for your inspection and intevention?

Thank you!