# Presentation: 034844

## Satellite Based Nowcasting of Convection

**Satellite Based Nowcasting of Convection**
**Initiation and Data Assimilation**

- John R. Mecikalski1, Kristopher M. Bedka2
- Simon J. Paech1, Todd A. Berendes1, Wayne M. Mackenzie1

*1**Atmospheric Science Department*
*University of Alabama in Huntsville*
*2**Cooperative Institute for Meteorological Satellite Studies*
*University of Wisconsin-Madison** *
**Supported by:**
**NASA New Investigator Program (2002)**
**NASA ASAP, SERVIR & SPoRT Initiatives**

## Outline

-  Convective Initiation research, validation & transition activities
-  NWS Products
-  Soil Moisture Initialization Research (data assimilation)
-  New Research, with NASA Data (lightning, MAMVs)

## CI

- Courtesy, NCAR RAP

**Lightning:**
**Type (CG, IC, CC)**
**Amount**
**Polarity**
**Altitude in clouds**
**with respect to anvil**

**Ambient Environment****:**
**Freezing level**
**(i.e. tropical vs. midlatitude)**
**CAPE (also, its shape) **

**Cumulus:**
**Cloud-top T**
**Cloud growth rate**
**Cloud glaciation**
**Freezing level:**
****** ****warm rain process**
****** ****ice microphysics**
**Interactions with ambient clouds (pre-existing**
**cirrus anvils) **

- Models/
- Sounders

- Satellite: VIS & IR

- LMA & NLDN

***CI***
*What are the factors?*

## Where We Are Now

** ****Applying CI algorithm over U.S., Central America & Caribbean**
** ****SATCAST/Flat ADAS to NWS HUN & MKX**
** ****SATCAST to NOAA/NESDIS & SPC**
** ****Validation & Confidence analysis**
** ****Satellite CI climatologies/CI Index: 1-6 h**
** ****Work with new instruments**
** ****Hydrological applications**

## CI Nowcast Validation

- Like any satellite-based weather decision-support product, false alarms do occur with the SATCAST nowcasting product
- VIS/IR Satellite observations only provide a “view from the top” and cannot retrieve in-cloud dynamics or thermodynamics, which can greatly influence cumulus evolution
- Cloud tracking errors using MESO AMVs
- An objective quantitative validation of the SATCAST nowcast product is challenging for several reasons
- 1) Parallax viewing effect causes difficulty in matching satellite observations with radar observed precipitation fields

- 2) Objective synchronization of current satellite cloud growth trends with future radar observations

- 3) Satellite navigation issues

## SATELLITE AMV WOULD INCORRECTLY FORECAST FUTURE RADAR ECHO LOCATION

**SATELLITE AMV WOULD INCORRECTLY FORECAST FUTURE RADAR ECHO LOCATION**

## Slide 7

## CI Nowcast Validation

- Conditional POD skill scores

## CI Nowcast Validation

## SATCAST Algorithm

***“******Interest Field” Importance***

| CI Interest Field | Critical Value |
| --- | --- |
| 10.7 μm TB (1 score) | < 0° C |
| 10.7 μm TB Time Trend (2 scores) | < -4° C/15 mins
∆TB/30 mins < ∆TB/15 mins |
| Timing of 10.7 μm TB drop below 0° C (1 score) | Within prior 30 mins |
| 6.5  - 10.7 μm difference (1 score) | -35° C to -10° C |
| 13.3 - 10.7 μm difference (1 score) | -25° C to -5° C |
| 6.5  - 10.7 μm Time Trend (1 score) | > 3° C/15 mins |
| 13.3 - 10.7 μm Time Trend (1 score) | > 3° C/15 mins |

-  Deep convection, dry upper troposphere.
-  Best for high CAPE environments, and strong updrafts.
-  Winter-time, Midlatitudes

## SATCAST Algorithm

***“******Interest Field” Importance***

| CI Interest Field | Critical Value |
| --- | --- |
| 10.7 μm TB (1 score) | < 0° C |
| 10.7 μm TB Time Trend (2 scores) | < -4° C/15 mins
∆TB/30 mins < ∆TB/15 mins |
| Timing of 10.7 μm TB drop below 0° C (1 score) | Within prior 30 mins |
| 6.5  - 10.7 μm difference (1 score) | -35° C to -10° C |
| 13.3 - 10.7 μm difference (1 score) | -25° C to -5° C |
| 6.5  - 10.7 μm Time Trend (1 score) | > 3° C/15 mins |
| 13.3 - 10.7 μm Time Trend (1 score) | > 3° C/15 mins |

-  Moist upper troposphere, “warm-top” convection. Shallow convection.
-  Low CAPE environments (tropical, cold-upper atmosphere). *f*(Physics)
-  Optimal in Tropics during summer.

## SATCAST Algorithm

***“******Interest Field” Importance: POD/FAR***

| CI Interest Field | Critical Value |
| --- | --- |
| 10.7 μm TB (1 score) | < 0° C |
| 10.7 μm TB Time Trend (2 scores) | < -4° C/15 mins
∆TB/30 mins < ∆TB/15 mins |
| Timing of 10.7 μm TB drop below 0° C (1 score) | Within prior 30 mins |
| 6.5  - 10.7 μm difference (1 score) | -35° C to -10° C |
| 13.3 - 10.7 μm difference (1 score) | -25° C to -5° C |
| 6.5  - 10.7 μm Time Trend (1 score) | > 3° C/15 mins |
| 13.3 - 10.7 μm Time Trend (1 score) | > 3° C/15 mins |

** ****Use of 8.5-11 & 3.7-11 ********m from MODIS have been considered**

-  Instantaneous 13.3–10.7 um:	**Highest POD (88%)**
-  Cloud-top freezing transition:	**Lowest FAR (as low as 15%)**
** ****Important for CI & Lightning Initiation**

## NWS Transition Activities

- SATCAST in AWIPS

**Web Survey 2007**
**NESDIS Operations**

- U. Wisconsin - CIMSS collaboration

## Outline

-  Convective Initiation research, validation & transition activities
-  NWS Products
-  Soil Moisture Initialization Research (data assimilation)
-  New Research, with NASA Data (lightning, MAMVs)

## NWS Transition Activities

- Flat ADAS for Surface Analyses

**Flat ADAS**

## NWS Transition Activities

- Mesoscale AMVs: *2007-2008*

## NWS Transition Activities

- CI “Trends of Trends”: *2007-2008*

## Satellite-Lightning Relationships

-       kkoooooooookkkkkkkkkkk

***Satellite-Lightning Relationships***

-  *Current Work:* Develop relationships between IR TB/TB trends and lightning source counts/flash densities toward nowcasting (0-2 hr) future lightning occurrence
** Supported by the NASA New Investigator Program Award #:NAG5-12536*

**2047 UTC**

**2147 UTC**

_**Northern Alabama LMA Lightning Source Counts**_

**2040-2050 UTC**

**2140-2150 UTC**

## CI Climatology Research

**GOES CI Interest Fields: 21 July 2005 (afternoon)**

- _Details:_
- 	-topography
- 	-main updrafts

**...****for LI**

**1 km Resolution**

## GOES-R Risk Reduction

- IR Window TB

- 8.5-11 μm Difference

- Deep Cu/Ice Cloud

- Cirrus Edge/Mid-Height Cu

- Clear Sky/Small Cu

- Semi-Transparent Cirrus

**Java-based Hydra Visualization Tool**

- Multispectral cloud properties are used to classify cumulus and identify clouds in a pre-CI state

_*8.5-11 *__**__*m Difference vs IR Window TB*_

## GOES-R Risk Reduction

***Preliminary MSG CI Nowcasting Criteria***

| CI Interest Field | Critical Value |
| --- | --- |
| 10.8 μm TB | < 0 K |
| 10.8 μm TB Time Trend | < -4 K/15 mins
TB/30 mins > TB/15 mins |
| Timing of 10.8 μm TB drop below 0° C | Within prior 30 mins |
| 8.5-10.8 μm TB Difference | < 0 K |
| 12.0-10.8 μm TB Difference* | -3 to 0 K |
| CAPE | > 500 J/kg |

-  Microphysical information from 1.6 reflectance is used to improve the convective cloud mask and negative 8.7-10.8 m differencing values are used to identify cumulus with liquid water tops

## MODIS/GOES Convective Cloud Mask Validation

- Visible Channel

- GOES Convective Cloud Mask

- MODIS Convective Cloud Mask

- Visible Channel

- GOES Convective Cloud Mask

- MODIS Convective Cloud Mask

## MODIS/GOES Convective Cloud Mask Validation

***In preparation for GOES-R***

- Visible Channel

- MSG Convective Cloud Mask

- MODIS Convective Cloud Mask

- Visible Channel

- MSG Convective Cloud Mask

- MODIS Convective Cloud Mask

## 1 Aug 2004 Soil Moisture Differences

_**0-10 cm**_

_**10-40 cm**_

_**40-100 cm**_

_**100-200 cm**_

_**ALEXI - EDAS**_

-  The largest differences between ALEXI and EDAS soil moisture occur over the eastern half of the study domain

-  The 40-100 cm soil layer shows that ALEXI soil moisture is wetter across a majority of the domain

-  The drier conditions in the 100-200 cm soil layer are once again in a region where vegetation is not able to extract water from the soil. The wetter conditions in SE OK are located within vegetation types which can extract water from this layer.

## ALEXI and EDAS Comparisons

- _ALEXI_

**RMSE = 0.059 or 19.7% f****AW**

- _EDAS_

**RMSE = 0.095 or 31.7% f****AW**

-  The retrieval of ALEXI soil moisture is compared to soil moisture observations from the Eta Data Assimilation System (EDAS) for each of the composite periods.

-  The EDAS soil moisture show substantial dry biases, with the largest bias occurring during observed wet soil moisture conditions (high fPET).

-  With respect to all observations during this period, the ALEXI soil moisture retrieval produces soil moisture estimates that exhibit a much lower RMSE than EDAS.

## Future Work

- Continue AWG GOES-R Risk Reduction
- Further Satellite based lightning initiation research using GOES, MODIS & MSG
- Thru NASA SERVIR, provide more hydrologic information from SATCAST
- Using MODIS NDVI product and topography maps, improve nowcasting 0-3 hours using vegetation and topography to determine areas where CI may occur. [*John Walker, UAH*]
- CloudSat, MODIS & QuikSCAT for convective momentum fluxes and mesoscale AMV assimilation [*Chris Jewett, UAH*]
- Peer-reviewed papers
- Additional soil moisture assimilation work: AMSR+MODIS via ALEXI [*Chris Hain, UAH*]; with the USDA
- Convective Climatologies [*2 UAH Graduate Students*]
- Collaboration with SPC [late 2007] & NOAA NESDIS
- Continued SATCAST validation + *transfer of MAMVs to NWS Huntsville*