# Presentation: 110679

## SOME EXPERIENCES ON SATELLITE RAINFALL ESTIMATION OVER SOUTH AMERICA: HYDROESTIMATOR TECHNIQUE

- <date/time>

**SOME EXPERIENCES ON SATELLITE RAINFALL ESTIMATION OVER SOUTH AMERICA: HYDROESTIMATOR TECHNIQUE**
** **
**Daniel Vila (dvila@essic.umd.edu)**
** **
** ****ESSIC/CICS – Computer & Space Science Building - Bldg #224**
**College Park, MD 20742**

## Outlines

-   Something about satellite rainfall estimation.
-   Brief algorithm description of the South American version of NOAA/NESDIS “Hydro-Estimator” satellite rainfall estimation and correction methodologies.
-   Image availability and convection activity.
-   Verification methods and some preliminary results over Del Plata basin.
-   Conclusions.

## Satellite Quantitative Precipitation Estimation (QPE) 

** ****1970s****   ------    Manual Procedures**
** ****1980s - 1990s****   ---- Interactive Methods / some use of**
**                                    ****microwave**
** **** ****2000****   ------    Single channel (10.7 mm) automatic algorithm**
**  ****2005****   ------    GOES multi-channel and microwave**
**  ****2008****   ------    Global Precipitation Measurement  (GPM) **
**                           ****Mission and GOES (postponed 2012?)**
**  ****20??****   ------    GPM and Hyperspectral (GIFTS) and GOES**
**              ****	****          ****Microwave?**
**                                     **

## Satellite Quantitative Precipitation Estimation (QPE) 

**Why Use Satellite QPE?**

-   **Superior spatial coverage**
**  ****Offshore coverage (tropical systems)**
**  ****No beam block problems**
**  ****Consistency**
**  ****Differences in calibration from radar to radar**
**  ****Radar range effects**
**  ****Beam overshoot (especially stratiform precip)**
**  ****Not a *****replacement*****, but a **_***companion***_** to radar**

## Satellite Quantitative Precipitation Estimation (QPE) 

**GOES-Based QPE:  Theory**

**Basis**
-   Assumes that cloud-top temperature ~ cloud-top height  cloud evolution   cloud-top thickness  rainfall rate
**Strengths**
-   24/7 coverage every 15 minutes throughout North America (this is not true in South America!!)
-   High spatial resolution (~4 km)
**Weaknesses**
-   Relationship between cloud-top properties and rain rate often does not hold, esp. for non-convective precipitation.
-   Cold cirrus can be mistaken for cumulonimbus.

## Satellite Quantitative Precipitation Estimation (QPE) 

**Microwave QPE Algorithms**

-   Special Sensor Microwave/Imager (SSM/I)—available since 1987
-   Advanced Microwave Sounding Unit-A (AMSU-A)—available since 1999
-   Advanced Microwave Sounding Unit-B (AMSU-B)—available since 2000
-   Tropical Rainfall Measuring Mission (TRMM) --- available since 1998

## Satellite Quantitative Precipitation Estimation (QPE) 

**Microwave QPE Algorithms Theory**

## Satellite Quantitative Precipitation Estimation (QPE) 

## Satellite Quantitative Precipitation Estimation (QPE) 

**Microwave-IR Blended Algorithm**

-   Relationship between 10.7- mm Tb and rain rate calibrated using SSM/I rain rate estimates
- “Best of both worlds”—combine robustness of MW estimates with availability of GOES data
-   Calibration updated every few hours for a 5x5-degree region
-   Uses all operational adjustments (moisture, orography, etc.)
-   Developed by F. J. Turk of NRL

## Program for the Evaluation of High Resolution Precipitation Products (PEHRPP)

**International Precipitation Working Group (Working Group of CGMS) found this an interesting and relevant problem, and agreed to sponsor and advise the effort    **(http://www.isac.cnr.it/~ipwg/)
*Hypotheses:*
-   HRPP errors can be characterized by comparing them to independent observations from rain gauges and radars.
-   Errors of and differences between HRPP are meaningful, in that they can be systematically related to precipitation characteristics and/or algorithm methodology.
-   Improved HRPP can be derived by combining products or methods based on the observed errors and differences.
-   HRPP spatial and temporal variability is realistic on scales appropriate for scientific studies (e.g., hydrology).
-   Numerical weather prediction forecasts of precipitation can be used to improve HRPP in some locations and times (e.g., high latitudes).

## Program for the Evaluation of High Resolution Precipitation Products (PEHRPP)

## Program for the Evaluation of High Resolution Precipitation Products (PEHRPP)

**http://www.cpc.ncep.noaa.gov/products/janowiak/us_web.shtml**

## Hydroestimator 

-   **Moisture correction**: precipitable water (PW) (integrated over the layer from surface to 500 hPa) and relative humidity (RH) (mean value between surface and 500 hPa., in percentage) obtained by ETA model are applied to decrease rainfall rates in dry environments and increases them in the moist ones.
-   **Orographic correction**: a Digital Elevation Model of South America at the GOES scale combined with low-level winds to produce an orographic correction to the satellite rainfall rate distribution.

**Hydroestimator **
**algorithm description**

## Hydroestimator 

-   **Clusterization**: Statistical parameters (average temperature and standard deviation) of each system is used to produce adjustments resulting in more realistic patterns of rain, especially for small-scale convection (CPTEC algoritm).
_**RAIN RATE ESTIMATION**_
-   Standardized temperature is defined as:

**Hydroestimator **
**algorithm description**

## Hydroestimator 

-   ***Conventive core: *** defined essentially by the empirical power-law function corrected by PW.

**  ****Tơ = 0**
***“******Non-core” precipitation:***  whose maximum value cannot exceed 12mmh-1 and must be less than the fifth part of the convective rainfall for a given pixel

-   **–****1.5 < Tơ < 0**

-  ** ****Tơ > 0  ******** pp = 0**

**Hydroestimator **
**algorithm description**

## Hydroestimator 

- Brigthness temperature - rainfall rate relationship for various values of precipitable water (mm) for convective core and for “non-core” precipitation

**Hydroestimator **
**algorithm description**

## Hydroestimator 

**Hydroestimator **
**algorithm description**

## Image availability 

- Image availability for southern hemisphere sector from 13 January 2003 to 28 February. Green boxes represent available images

## Image availability 

**Image availability**** **

## Image availability 

**Continent Will Benefit from Emerging Global Earth Observation Network**
- Jan. 18, 2006 — In Buenos Aires on Tuesday, _[NOAA](http://www.noaa.gov/)_, the _[Comisión](http://www.conae.gov.ar/principal.html)__[ ](http://www.conae.gov.ar/principal.html)__[Nacional](http://www.conae.gov.ar/principal.html)__[ de ](http://www.conae.gov.ar/principal.html)__[Activades](http://www.conae.gov.ar/principal.html)__[ ](http://www.conae.gov.ar/principal.html)__[Espaciales](http://www.conae.gov.ar/principal.html)_, and the _[World Meteorological Organization](http://www.wmo.int/index-en.html)_ announced news of the repositioning of GOES-10. Shifting the spacecraft from its current position above the equator in the West to a new spot in orbit will greatly improve environmental satellite coverage of the Western Hemisphere, especially over South America. The repositioning is planned for October 2006 pending the successful launch of GOES-N, NOAA's new _[geostationary satellite](http://www.oso.noaa.gov/goes/)_, and the continued operation of GOES-12.
- (extracted from NOAA News Online - http://www.noaanews.noaa.gov/stories2006/s2561.htm

**Image availability**** **

##   Verification methods

**  ****Verification methods**

##   Verification methods

**  ****Verification methods**

##   Preliminary results

_**EXPERIMENT DESIGN**_
-  ** ****Period**: January - February 2003
-   **Region**: Del Plata basin (40°S - 20 °S, 60°W - 35 °W)
-   **Image availability**: more than 28 images in 24 hours. 27 cases were selected
-   **Ground truth**: Raingauges  (INMET meteorological stations, PCDs and other networks)
-   **Integration method**: cubic splines time interpolation.

##   Preliminary results

**  ****Preliminary results**

##   Preliminary results

**  ****Preliminary results**

##   Preliminary results

**  ****Preliminary results**

##   Case study (1)

***21 January 2003***

##   Case study (1)

- Overall statistics for 20-21 January 2003. Underestimation is present in all intervals for both algorithms.

***NESDIS algorithm (available in INTERNET)***

**  ****Case study (1)**

##   Case study (1)

**  ****Case study (1)**

##  Case study (2)

** ****Case study (2)**

##  Case study (2)

** ****Case study (2)**

##  Case study (2)

** ****Case study (2)**

## Cuareim River Basin

**Cuareim River Basin**

-   24-hours rainfall estimation using HE technique (NESDIS version)
-   Period: March 1st 2002 – July 31st 2003
-   Calibration data: GTS available raingauges
-   Validation data: CTMSG raingauge network

## Cuareim River Basin

**Cuareim River Basin**

## Cuareim River Basin

- Schematic procedure of the best adjusted value (MVE). Rainfall data is compared with a nine pixels kernel centered in the rain gauge location

**Cuareim River Basin**

## Cuareim River Basin

**Cuareim River Basin**

- Scatterplot of Observed vs. Estimated mean areal rainfall corrected with rain gauges values.

## Statistical Summary

-  The results of the corrected spatial precipitation estimates improve noticeably with respect to those without correction.

##  Case study (3)

** ****Case study (3)**

##  Case study (3)

** ****Case study (3)**

##   Conclusions

-   The main purpose of this work is to present the recent improvements of the Auto-Estimator Algorithm (Hydroestimator) and the application of this technique in Del Plata basin (South America).
-   The main difference between the South American model and the one for North America is the image availability. Gaps up to three hours in South America imagery may be a very important factor in the accuracy of the estimations.
-   The errors involved in these kind of techniques were evaluated during January-February 2003 (summer) and the case study presented.
-    More detailed statistics (i.e. warm and cold tops discrimination and seasonal behavior) will be carried out in the future.

## MUCHAS GRACIAS !!!

**THANK YOU !!!**