# Presentation: 694652

## Folkert Boersma, Henk Eskes, Pepijn Veefkind and Ellen Brinksma

- (D)OMI NO2: the KNMI near-real time product

## Contents

-  Purpose and context
-  Near real-time retrieval algorithm
-  Results
-  Validation

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Purpose (1)

-  To provide users with near-real time air pollution monitoring
-  Users include:	- environmental agencies
- 		- air quality forecasters
- 		- GEMS (EU GMES) lead by ECMWF
- 		- PROMOTE (ESA GMES)
- 		- ...

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Purpose 2

- To generate a long-term consistent dataset from:
- 	- GOME (1996-2003)
- 	- SCIAMACHY (2003-    )
- 	- OMI (2004-    )
- KNMI retrieval algorithm for tropospheric NO2
-  Data publicly available via _[www.temis.nl](http://www.temis.nl/)_
-  Described in Boersma et al. (*JGR*, D04311,2004)
-  Lightning NO2 production (*ACP*, **5**, 2005)

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Near real time retrieval algorithm

- Post-processing (GOME/SCIA)
- Retrieval/assimilation/modelling

- NRT (OMI)
- Retrieval + assimilation/modelling

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Branch 1: TM4 forecast

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Branch 2: NRT retrieval

- De nieuwe generatie: OMI

- NASA/KNMI DOAS algorithm

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## NRT retrieval ‘operational’ since 7 October 2005

- Images available within ~2hrs (www.temis.nl/airpollution/)
- 	- data acquisition
- 	- downlink
- 	- processing
- 	- KNMI/NASA DOAS algorithm
- 					~2 hrs
- 	- NRT processing time:		< 2 minutes

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Stripe correction

- 1. Find window with smallest variation in initial columns

- 2. Compute mean column vs. across track viewing angle

- 3. FFT analysis to smooth

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Stripe correction

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Comparison with CHIMERE

- Cloudy pixels masked

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Saturday

- Sunday

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Dandelions validation (in progress)

- r = 0.59 (n=14)

-  14 separate orbits
-  DOMINO > MAXDOAS
-  Representativity issues

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Conclusions

-  OMI NO2 near-real time retrieval operational
-  Initial comparisons to:	- CHIMERE
- 			- MAXDOAS
- Outlook
-  Validation vs. SCIAMACHY and official OMI NO2 product
-  clouds
-  stripe correction

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## 1. ‘Rural’ comparison

- Criteria
-  OMI pixel w<50% (fcl <0.2)
-  t< 1 hr
-  r< 25 km

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## ‘Rural’ comparison – Schipluiden

- ‘Rural’ comparison – Schipluiden

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## ‘Rural’ comparison – Westmaas

- ‘Rural’ comparison – Westmaas

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## ‘Rural’ comparison – Cabauw

- ‘Rural’ comparison – Cabauw

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## ‘Rural’ comparison – Hellendoorn

- ‘Rural’ comparison – Hellendoorn

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## ‘Rural’ comparison – Kollumerwaard

- ‘Rural’ comparison – Kollumerwaard

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## ‘Rural’ comparison 

- ‘Rural’ comparison

- All stations (>20)
-  Calculate average OMI column for corresponding to surface concentrations
-  Standard deviation of the mean is a measure for uncertainty on OMI average
-  Calculate correlation coefficient
-  Calculate weighted least square fit y = a +bx

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## ‘Rural’ comparison 

- ‘Rural’ comparison

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## ‘Urban’ comparison 

- ‘Urban’ comparison

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Street station comparison 

- Street station comparison

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Preliminary conclusions

-  First (Dutch) OMI NO2 ‘validation’ result of ‘old’
-  For NL: good average correlations (r= 0.6-0.9)
-  Clear relationship between surface NO2 conc. and OMI columns

- Discussion

-  Offset too large: 3-7 1015 molec. cm-2
-  Use boundary layer height to convert conc.  column
-  ‘Old’ OMI dataset (new OPF, cloud algorithm improvements)

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## NO2

**NO****2**

**NO****2**

**NO****2**

**NO****2**

**NO****2**

- Atlas der Schweiz interaktiv © 2003 swisstopo (BA035204)

- 2. Column comparison ground-based in-situ  space-borne

## NO2

- PBL

- TROPOPAUSE

**NO****2**

**NO****2**

**NO****2**

**NO****2**

**NO****2**

- Atlas der Schweiz interaktiv © 2003 swisstopo (BA035204)

- 2. Column comparison ground-based in-situ  space-borne

## NO2

- PBL

- TROPOPAUSE

**NO****2**

**NO****2**

**NO****2**

**NO****2**

**NO****2**

**NO****2**

**height**

**advection**

- Atlas der Schweiz interaktiv © 2003 swisstopo (BA035204)

- 2. Column comparison ground-based in-situ  space-borne

## 2. Comparing GOME and in-situ ‘profiles’

- GOME:
- Validation:                                   	with
- GOME/Validation:

- For every collocation comparison through the kernel

## 2. Averaging kernel

- alb = 0.05
- alb = 0.20
- cloud at 800 hPa

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## 2. GOME NO2 validation – cloud-free 

|  |  |
| --- | --- |

-  GOME 1996-2003
-  Cloud-free scenes
-   n~100

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## 2. GOME NO2 validation – cloud-covered

|  |  |
| --- | --- |

-  GOME 1996-2003
-  Cloud-covered scenes
-   n~25
-  open: via kernel
-  solid: vertical integral

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## 2. Conclusions

|  |  |
| --- | --- |

-  Vertical profiles can be constructed from in-situ ground-based data
-  Validation through kernel 
- 	Comparison becomes independent on a priori profile
-  Preliminary results show excellent agreement
-  Representativity issues 
- 	What part of difference is caused by differences in temporal/spatial sampling?

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Comparison SCIA – ground-based DOAS Bologna

- Petritoli et al., 2005

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Slide 35

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Slide 36

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Slide 37

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Slide 38

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate

## Slide 39

**Notes:**
GOA is a project in which a.o. IUP and KNMI participate