# Presentation: 830604

## Climate Downscaling                                  Techniques

- Marina Timofeyeva
- UCAR/NWS/NOAA

## TALK OUTLINE

-  What is Downscaling
-  NWS NCEP CPC climate outlooks and 	regional climate
-  Downscaling methods
-  Application of CPC methods in Developing 	Local Climate Products
-  Messages to take home

## DOWNSCALING

- DOWNSCALING is the transformation from a LARGE SCALE feature to a SMALL SCALE one (not necessarily of the same kind).
- DOWNSCALING implies increases resolution of output.

## NWS NCEP CPC weather & climate outlooks

## NWS NCEP CPC climate outlooks

- This is a map of 344 climate divisions currently in use over the U.S. Note the changing size as one goes from east to west, as well as from one state to another.

- CPC uses 102 mega or forecast divisions in their forecasts. The divisions in the West closely correspond to NCDC climate divisions.

## NWS NCEP CPC climate outlooks

## NWS NCEP CPC climate outlooks

- National precipitation map based on high-resolution PRISM data (left) and on Climate Divisions (right). Note the large gradients and fine-scale variability in the Western U.S. that is not reproduced in the right map.

**Precipitation Climatology 1971 - 2000**

***Slide courtesy of Klaus Wolter, CDC***

## NWS NCEP CPC climate outlooks and 

- Official CDs for Colorado (left) and Experimental CDs (right) based on multivariate statistical analysis of climate data that also include SNOTEL data. Such new CDs are being derived for the entire U.S.A.

- NWS NCEP CPC climate outlooks and
- Regional Climate

***Slide courtesy of Klaus Wolter, CDC***

## NWS NCEP CPC climate outlooks and 

- Regional Climate

- # of stations that
- did not reject the test H0

- If climate at station is the same as at climate division, then mean and variance at station and climate divisions should be the same. THEY ARE NOT!

## NWS NCEP CPC climate outlooks and 

**NUMBER OF STATIONS (OUT OF 9) THAT HAVE SQUARED CORRELATION WITH CD >=0.8**

- NWS NCEP CPC climate outlooks and
- Regional Climate

## DYNAMICAL DOWNSCALING

**DYNAMICAL DOWNSCALING**

## DYNAMICAL DOWNSCALING

**DYNAMICAL DOWNSCALING**

## DYNAMICAL DOWNSCALING

-  ETA and AVN are examples on meteorological 	scale
-  Climate applications:
-  Regional Spectral Model (RSM) and Seasonal Forecast Model (SFM)
-  Nested in T62 and T40 NCEP coupled AOGCM using 50, 30 and 20 km resolution grids
-  tested for 1997 winter El Nino
-   results:
-  RSM shows improvement in temperature forecast in comparison with AOGCM
-  “50-km RSM is _unable_ to forecast anomalies over high mountains”
-  20-km RSM provides “realistic distribution of precipitation”, but _overestimate_ its maxima

**DYNAMICAL DOWNSCALING**

## STATISTICAL DOWNSCALING

**WEATHER GENERATORS**

- Climate
- observations

- Statistics

- Climate
- predictions

- Global
- Circulation
- Pattern
- predicted

- Statistics

- Class

**Calibration**

**Prediction**

- Frequency
- analysis

- Global
- Circulation
- Pattern
- observed

## STATISTICAL DOWNSCALING

- CORRELATION MODELS

- Climate
- Observations

- GCM fields

- Statistics

- Statistics

- Statistical relationship

- Modeled climate
- Statistics

**Prediction**

**Calibration**

## APPLICATION OF CPC METHODS  IN DEVELOPING LOCAL CLIMATE PRODUCTS

-  Western Region HQ (Andrea Bair)
-  NWS OCWWS CSD (Marina Timofeyeva)
-  NWS NCEP CPC (David Unger)

## Utilized CPC Methods of Downscaling

- Use of composites in the forecast of local climate using climate variability modes

- Translation of probability of exeedance (POE) outlooks from climate divisions to local station temperature forecasts

## Utilized CPC Methods of Downscaling

** **

**Temperature Outlook **
**  ****Precipitation Outlook **
**Degree Day Outlook**

**Temperature Outlook **
**Precipitation Outlook **
**Degree Day Outlook**

## Utilized CPC Methods of Downscaling - POE

- Utilized CPC Methods of Downscaling - **POE**

- POF (%)

- Translation of forecast division POE to station forecast was developed in CPC by Barnston, Unger, and He. The POE outlooks became available  in December 1994, and the translations to station temperature in 2000.

- Observed T

## Utilized CPC Methods of Downscaling - POE

- Utilized CPC Methods of Downscaling - **POE**

## Utilized CPC Methods of Downscaling - POE

- Step 1: Defining stations where the station outlooks are used

## Utilized CPC Methods of Downscaling - POE

- In most cases there is a strong relationship between temperature at station (y axis) and climate division (x axis).

- Step 2: Developing regression equations for those stations

## Utilized CPC Methods of Downscaling - POE

- Utilized CPC Methods of Downscaling - **POE**

- Step 2: Developing regression equations for those stations
- Regression coefficients are adjusted for the trend

**years**

**Difference** **Tstation – Tcd **(oF)

## Utilized CPC Methods of Downscaling - POE

- Step 3: Test of regression equations stability - Cross validation

| Calibration data set | Verification Year |
| --- | --- |
| 1971 | 1971 |
| 1972 | 1972 |
| 1973 | 1973 |
| 1974 | 1974 |
| 1975 | 1975 |
| ... | ... |
| 1997 | 1997 |
| 1998 | 1998 |
| 1999 | 1999 |
| 2000 | 2000 |

- Cross validation allows expansion of the test sample and protects against over fitting

## Utilized CPC Methods of Downscaling - POE

| Calibration data set | Verification Year |
| --- | --- |
| 1971 | 1971 |
| 1972 | 1972 |
| 1973 | 1973 |
| 1974 | 1974 |
| 1975 | 1975 |
| ... | ... |
| 1997 | 1997 |
| 1998 | 1998 |
| 1999 | 1999 |
| 2000 | 2000 |

- Utilized CPC Methods of Downscaling - **POE**

- Step 3: Test of regression equations stability - Cross validation

## Methods for Climate Forecast Verification

- Ranked Probability Score  and Continuous Ranked Probability Score

- The Rank Probability Score (RPS), graphically represents the performance of the probability forecast (Wilks, 1995).

- RPS is not sensitive for forecast spread.

**Tobs**

- Continuous Rank Probability Score (CRPS) takes into account spread of the forecasted distribution.

- CRPS Skill Score (CRPSS) is the final measure of the forecast performance.

## Progress Report - CRPSS

## Methods for Climate Forecast Verification

- Reliability Diagrams

**Reliability Diagrams exhibit the correspondence between the observed and forecasted percentiles.  Reliability Diagrams allow verification of each POE for each station. The analysis is done for a forecast and compared with climatology.**

- Under-forecasting

- Over-forecasting

## Progress Report – Reliability Diagrams

## Methods for Climate Forecast Verification

- Bias Analysis

**The bias is computed for CPC forecasts and for climatology using the equation shown on the right for climate divisions and stations for each forecast month and each lead season. The bias shows range and sign of deviations between forecasts and observations.  Mean Square Error (MSE) is other common accuracy measure of climate forecast leading to skill score (SS) estimates.**

**Expected PDF of difference between forecasts and observation is normal distribution with mean that is not significantly different from 0.**

## Utilized CPC Methods of Downscaling - POE

- When this method fails...

## Utilized CPC Methods of Downscaling - POE

- When this method fails...

*R – **Measure of Confidence in Downscaling*

***ρ  ***

**Station Forecast Spread**

## Utilized CPC Methods of Downscaling - POE

- When this method fails...

- Mean = 0.30
- St. Dev.= 0.38
- Median = 0.19
- Mode = 0.01
**Skewness = 3.11**
**Kurtosis = 14.67**

*NOT a*
*good fit*

- Temperature is a normally  distributed variable, therefore the downscaling method based on regression can provide good estimates

- Precipitation (right chart) is too skewed for normal distribution.  The regression would require a transformation of this variable.  Compositing can be used for Precipitation forecasts because it does not employ regression analysis.

## Utilized CPC Methods of Downscaling – 

- Composite means
- Raw Composite distribution
- Smooth resampled Composite Distribution - boot strapping techniques
- All of the above with trend and some other mode of climate variability taken into  account using new approach developed by Higgins, Unger and Kim

- Utilized CPC Methods of Downscaling –
**COMPOSITES**

## Utilized CPC Methods of Downscaling – 

- Utilized CPC Methods of Downscaling –
**COMPOSITES**

## Utilized CPC Methods of Downscaling – 

**COMPOSITES – level 1**

## Utilized CPC Methods of Downscaling – 

**COMPOSITES – level 2**

## Utilized CPC Methods of Downscaling – 

**COMPOSITES – level 2**

|  | B | N | A |
| --- | --- | --- | --- |
| Jan | 1 | 3 | 5 |
| Feb | 1 | 4 | 4 |
| Mar | 5 | 3 | 1 |
| JFM | 0 | 7 | 2 |

**FORECAST**: Given El Nino, Denver Tmean has a shift in Tmean toward above normal for Jan, below normal for Mar, and near normal for JFM

## Utilized CPC Methods of Downscaling – 

|       Nino3.4

Term | Warm | Neutral | Cold |
| --- | --- | --- | --- |
| Above | 2/9=0.22 | 9/32=0.28 | 2/9=0.22 |
| Near | 7/9=0.78 | 12/32=0.38 | 4/9=0.45 |
| Below | 0/9=0 | 11/32=0.34 | 3/9=0.33 |

- JFM composites

- For each Nino 3.4. event we compute probability of the climate variable to be in Below/Near/Above normal category.

- Utilized CPC Methods of Downscaling –
**COMPOSITES – level 2**

## Utilized CPC Methods of Downscaling – 

- CPC CURRENT ENSO FORECAST:
- _[http://www.cpc.ncep.noaa.gov/products/precip/CWlink/ENSO/total.html](http://www.cpc.ncep.noaa.gov/products/precip/CWlink/ENSO/total.html)__ _

- NINO 3.4  INITIAL TIME   3 2003
- PROJECTION FRACTION
-         		BELOW	NORMAL	ABOVE
- AMJ	1	0.039 	0.372 	0.589
- MJJ	2 	0.066 	0.446 	0.488
- JJA 	3 	0.126 	0.494 	0.380
- ...
**JFM ****	****9****	****0.343****	****0.434****	****0.243**
- FMA	10 	0.318	0.438	0.244

|     Nino3.4

Term | Warm | Neutral | Cold |
| --- | --- | --- | --- |
| Above | 2/9=0.22 | 9/32=0.28 | 2/9=0.22 |
| Near | 7/9=0.78 | 12/32=0.38 | 4/9=0.45 |
| Below | 0/9=0 | 11/32=0.34 | 3/9=0.33 |

**Example – ElNino with 8.5 month lead (forecast for JFM 2004):**

- Utilized CPC Methods of Downscaling –
**COMPOSITES – level 2**

## Utilized CPC Methods of Downscaling – 

**COMPOSITES – level 3**

| El Nino Years | January | February | March |
| --- | --- | --- | --- |
| 1958 |  |  |  |
| 1966 |  |  |  |
| 1969 |  |  |  |
| 1973 |  |  |  |
| 1983 |  |  |  |
| 1987 |  |  |  |
| 1992 |  |  |  |
| 1995 |  |  |  |
| 1998 |  |  |  |

**X**

**X**

**X**

**X**

**X**

**X**

**X**

**X**

**X**

**X**

**X**

**X**

- To obtain a smooth distribution we can use resampling, which allows 93 = 729 different combinations of the months in each season.
- To better represent extremes in the distribution we sample with replacement using boot strapping technique.

## Utilized CPC Methods of Downscaling – 

**COMPOSITES – level 4**

- DJF North Dakota Temp (°C)

- The trend should not be removed arbitrarily.  Hinge, for example, explains climate changes  during the last decades. 11-year Moving Average (MA) explains decadal variations in climate.

## Research Products Versus Operational Products

| Method | Research Output | Operational Products |
| --- | --- | --- |
| POE | Regression equation coefficients

Method performance evaluation based on hind cast applications (1995-2003) | Seasonal forecasts issued monthly for 13 seasonal leads using equations and CPC CD forecasts

Verification issued monthly for forecast made in preceding month   |
| Composites | All composite statistics: mean, variance, each category probabilities with and without trend,  and POE.

Method performance evaluation based on hind cast applications (1982 – 2003) | Seasonal forecasts issued monthly for 16 seasonal leads using station statistics and CPC Nino 3.4. forecasts

Verification issued monthly for forecast made in preceding month |

## WR NEW LOCAL CLIMATE PRODUCTS

- Where do we go...

**EXPECTED OPERATIONAL FUNCTIONS: REGIONAL CSPM**
**1. POE downscaling**
-     1.1. Developing the translation equations for 87 sites (completed)
-     1.2. Tests of the equations (2003-2004)
-     1.3. Monthly coordination of local product release (starting 2005)
-     1.4. Annual update of the equations (starting 2005)
**2. Composites**
-     2.1. Coordination of Composites products existing or released in 	the local offices
-     2.2. Developing Composites for 87 sites (2003-2004)
-     2.3. Hind cast test of the composites (2003-2004)
-     2.4. Monthly coordination of local product release (starting 2005)
-     2.5. Annual update of the composites (starting 2005)

## WR NEW LOCAL CLIMATE PRODUCTS

- Where do we go...

**EXPECTED OPERATIONAL FUNCTIONS: WFO CSFP **
**1. POE downscaling: **
-     1.1. Selection of sites within WFO CWA for downscaling  (completed)
-     1.2. Delivering on monthly basis seasonal outlooks for selected
- 	sites within WFO CWA (starting in FY05)
-     1.3. Verification of the previous month forecasts (starting in FY05)
**2. Composites: **
-     2.1. Keeping self updated on climate variability mode status
- 	(starting in October 2003)
-     2.2. Developing composites local studies (optional)
-     2.3. Release of  monthly and seasonal outlooks for selected
- 	sites within each WFO CWA (starting in 2005)
-     2.4. Verification of the Composites forecasts (starting in 2005)
**3. Public outreach on these new products**

## MESSAGES TO TAKE HOME

-  THERE ARE NO _NWS CONSISTENT__ __LOCAL__ __CLIMATE _	_PRODUCTS_ AVAILABLE _NOW_
-  DOWSCALING CAN BE USED AS A TOOL FOR  LOCAL 	CLIMATE PRODUCTS
-  THE LOCAL CLIMATE PRODUCT SHOULD BE CONSISTENT 	WITH THE NATIONAL WEATHER SERVICE PRODUCTS 	(CPC)
-  CPC METHODS COULD BE USED IN DEVELOPING SUCH 	LOCAL CLIMATE PRODUCTS
-   IN DEVELOPING OF DOWNSCALING AT LEAST THREE NWS 	ENTITIES SHOULD BE INVOLVED: REGIONAL OFFICE, 	CSD, AND CPC