An intraseasonal moisture nudging experiment in a tropical channel version of the WRF model: The...

An intraseasonal moisture nudging experiment in a tropical channel version

of the WRF model: The model biases and the moisture nudging scale

dependencies

Marcela Ulate

University of Miami

The MJO Case of Study

LON

TIM

E

mm

/day

TRMM

m/s

U850 Anom. ERA-Interim

TRMM Precipitation NOAA OLR

TRMM Daily Precipitation Anomalies (Filled Contours) and NOAA Daily Outgoing Longwave Radiation Anomalies (Line Contours: Blue negative anomalies, :Red positive anomalies).

Model Description

• WRF v3.2• 1º x 1º horizontal resolution.• 28 vertical levels.• Tropical channel domain:

Periodic Boundary conditions in the east-west direction.

• Boundary Conditions form ERA-Interim data

Model Physics:Microphysics: WSM3-class simple ice schemeLongwave Radiation: rrtm schemeShortwave Radiation: Dudhia schemeLand Surface Model: Noah Land Surface ModelBoundary Layer: Mellor-Yamada-Janjic scheme

The Dry Bias in WRF

The dry bias

WRFRH – ERAIRH

P (h

Pa)

Days

P (h

Pa)

Lat Lon

P (h

Pa)

Approach to the problem: Humidity Nudging

• Four-Dimensional Data Assimilation (FDDA) or nudging is the process where the model is set to converge at a desired rate to the analysis or observations.

• The process adds an extra tendency term to the model equations proportional to the difference between the model simulation and the analysis value at every grid point, forcing the simulation closer to the analysis value.

Humidity Nudging

€

∂α∂t

= F(α ) + GαWα ( ˆ α 0 −α )

From Skamarock et al. 2008.

Model forcing terms Nudging Tendency term

€

Gα : nudging factor ,

€

Wα: four dimensional weight function,

€

ˆ α 0:analysis field value

€

Gα = 3.0x10−6 s

€

TG =1

Gα

= 3.85days

WRFRH – ERAIRH

P (h

Pa)

Days

P (h

Pa)

Lat Lon

P (h

Pa)

Reduction of the dry bias

Grid Nudging

Variations of Nudging Vertical Weight Function

Z P

Above PBL Vertical FDDA Weight Function (Default)

Weight Function Weight Function

Z P

Above PBL Vertical FDDA Weight Function

Weight Function Weight Function

High

Mid

Low

Low

Mid

High

Z P

Fixed Vertical FDDA Weight Function

Weight Function Weight Function

High

Mid

LowLow

Mid

High

€

k pblt ,IO ≈ 7 =>~ 900m

Grid Nudging: Vertical Weight Function

Spectral Nudging of Humidity

Spatially filter the data (minimum x,y wavelength)

Analysis data (ERA-Interim)

Nudging Tendency

Spectral Nudging: Remove long wavelengths (small wave numbers)

Spectral Nudging: Remove short wavelengths (high wave numbers)

Spectral Nudging: Remove specific wavelength (specific wave numbers)

• Removing the short wavelengths (high wave numbers) improves the control simulations.

• Mean and Long wavelengths are important in order to improve the MJO simulation.

• The model “needs” to resolve the moisture large scales-structures well enough in order to obtain a MJO-like event.

TIM

E

LON LON

“MJO LINE”

Humidity Tendency due to nudging

Humidity Tendency due to cumulus scheme MJO-like precipitation simulation

Humidity Tendency due to cumulus scheme - CONTROLP

(hPa

)P

(hPa

)g/Kg day-1

g/Kg day-1

Heating Tendency - Control

Heating Tendency – MJO-like precipitation simulation

P (h

Pa)

P (h

Pa)

K/day

K/day

How much nudging is too much nudging?What if Ga=1 ?

6 year WRF Simulation

(Same Configuration)

a) b)

c) d)

e) f)

MAYOCT NOVAPRObservations

a) b)

c) d)

e) f)

MAYOCT NOVAPRWRF

a) b)

c) d)

ERAI, TRMM WRF

ConclusionsSpectral and grid Nudging of water vapor mixing ratio reduces the

model dry-bias and allows the model to produce an improved MJO-like precipitation pattern and wind signal.

The moisture at mid levels of the troposphere is crucial in order to reproduce the convective signal associated with the MJO.

Without nudging, the cumulus schemes remain relative inactive i.e. lack of precipitation during the MJO event. This translates to a weak heating profile. When the MJO precipitation pattern improves, the heating profile resembles the results of other studies more closely.

The prediction of the first MJO event improves when nudging is preformed, while the initiation of the second event is not for some cases. This suggests that improving the humidity field is one component of the problem, and we need to investigate further on this matter.