# Presentation: 310735

## Introduction of temperature observation of radio-sonde in place of geopotential height to the global three dimensional variational data assimilation system in JMAA.NaruiJapan Meteorological Agency, Japan

## content

- I. The reason to introduce temperature observation of radio-sonde in place of geopotential height
- II. modification  to assimilate temperature
- III. Forecast experiments
- IV. summary

## I.The reason to introduce temperature observation of radio-sonde in place of geopotential height 

-  The global three dimensional variational data assimilation system (3D-Var) was implemented in JMA operation in September 2001.
-   The direct assimilation of ATOVS radiances was introduced in May 2003.
-  As the next step for our 3D-Var, we have a plan to introduce _variational quality control (VarQC)_. Because VarQC is natural extension of variational method.
-   Since it is favorable for VarQC that there is no correlation between observation data, we are going to assimilate temperature of radio-sonde in place of geopotential height, which has strong vertical correlation.

## I.The reason to introduce temperature observation of radio-sonde in place of geopotential height 

-   Though the main purpose of this work is to prepare for the introduction of VarQC, the use of temperature data itself showed some _good impacts_ on the forecast score.

## SYSTEM  OF JMA/3D-VAR

- FORECAST MODEL :  GLOBAL MODEL
- RESOLUTION:  T213L40 (OUTER MODEL)
-                                T106L40 (INNER MODEL)
-                               INCREMENTAL METHOD
- ANALYSIS VARAIBLE: ζ、D、T、Ps、ln q
- CONTROL VARIABLE: ζ、Du、(T,Ps)u、ln q
- BACKGROUND ERROR: NMC METHOD for 2000
-                                                HOMOGENEOUS
- MINIMIZATION: LBFGS

## II.modification to assimilate temperature

- 1. remove the vertical correlation of observational errors for all elements
- 2. use the significant level data in addition to the standard level data
- 3. recalculate all observational errors for all elements of radio-sonde from the statistics of observation departure from the background

## III. Forecast experiments

**Exp.1: assimilation of geopotential height**
**Exp.2: assimilation of temperature**
**Forecast Model:Global Model T213L40**
**6hourly cycle**
**                         ****period 1                          period 2**
**assimilation 27Jun-30July 2002     27Nov-31Dec 2002**
**initial           12UTC 1-21 July        12UTC 1-21 Dec**
**Fcst range    216 hour                      216 hour**

## Analysis increment of sea level pressure00UTC 3rd July 2002 in N.H.left:temperature                       right:height

## Anomaly correlation of 500hPa height  2002   7/1~7/21 (against initial field)blue:heightred:temperature Global       NHTropics      SH

## Anomaly correlation of 500hPa height 2002   12/1~12/21 (against initial field) blue:heightred:temperature Global       NHTropics      SH

## RMSE and Bias of 500hPa height  2002   7/1~7/21 (against radio-sonde) green:heightred:temperature left:rmse    right:biasNHTropics SH

## vertical profile of temperature 2002 12/31(after one month anlalysis cyclemean of Northern Hemisphere) green:heightblack:temperature

## IV. Summary

- 1. We Introduced temperature of radio-sonde in place of geopotential height.
- 2. There is some good impact on forecast score.
- 3.Problem: Bias against radio-sonde
- 4. VarQC is developed now.

## Example of VarQC  

- Formulation  (including gross error probability)Cost function: JOQC =-l n[(γ+exp(ーJON) )/(γ+ 1)]∇JOQC = ∇JON ×(1-P)  JON : normal cost function γ : VarQC parameter for each observationP: gross error probabilityOIQC: oprerational QC in JMAcompare each datum in turn against an analysis based on surrounding data with OI

## Example of VarQC rejected with VarQC(gross error probability is >75%)

- Example of VarQC **rejected with VarQC(gross error probability is >75%)**

- Analysed surface pressureupper:increment  left:VarQC        right:OIQC Lower:   left:difference  right:analysed field

## The End