# Presentation: 472394

## Anthropogenic Climate Changes in California: Hydroclimate, Snowpack, and Santa Ana Winds 

**Anthropogenic Climate Changes in California: ***Hydroclimate, Snowpack, and Santa Ana Winds *

_**JPL**_*: Duane Waliser, Yi Chao, Qinbin Li, Annmarie Eldering*
_**UCLA**_*: Jinwon Kim, Kuo-Nan Liou,Yongkang Xue, Alex Hall, *
*Mimi Hughes, Sarah Kapnick, Robert Fovell, Jim McWilliams*

**5th Annual California Climate Change Conference**
**Sacramento Convention Center September 8 - 10, 2008**

- www.jifresse.ucla.edu

## Outline

- UCLA + JPL Joint Institute
- JIFRESSE Research Foci & Objectives
- Regional Model Development & Framework

- Today’s California Climate Change Themes
-  Hydroclimate *(Kim et al. 2008; poster & paper)*
-  Sierra snowpack & snow physics *(Kapnick and Hall, 2008; Waliser et al. & Kim et al. 2008; posters & papers)*
-  Santa Ana wind conditions *(Hughes et al. 2008; poster and paper)*

- Summary and Future Work

## California Climate Change: UCLA+JPL

- In 2006, UCLA & JPL established a _Joint Institute for Regional Earth System Science & Engineering_ (JIFRESSE) to promote, stimulate, and engage UCLA *(Modeling)* and JPL *(Observations) *in cutting edge Earth System science research to:

- Increase understanding about factors that affect climate-related environmental changes, with particular attention to regional/CA issues;
- Support the design of future JPL/NASA space missions & observation networks related to detecting, monitoring, and projecting climate changes;
- Enhance the educational mission of UCLA through collaboration with JPL.* *

- www.jifresse.ucla.edu

## California Climate Change: Motivation

*Apply our unique strengths in system engineering and observations (JPL) and process understanding and modeling (ULCA) to improve our capabilities to detect and predict changes in California’s climate and ecosystems and contribute to the State’s awareness and understanding, and adaptation and mitigation strategies.*

**IPCC AR4 model projections agree that California will warm in this century but disagree on whether it will become wetter/drier.  This implies that some physical processes are inadequately represented in GCMs.**

## California Snowpack Change: Motivational Study

- A snow water equivalent dataset was developed from 1930 -2007.

-  For each winter season, the date of peak snow mass was calculated.

- Kapnick & Hall, 2008

- Trend: date of peak snow mass occurs earlier by 0.4 days per decade.

- Based on these results and considerations of temperature projections, the date of peak snow mass would be expected to occur 3-9 days earlier by end of century.

## California Snowpack Projections: Model Uncertainties

- What do the models (directly) project?

- These are the types of questions JIFRESSE is addressing.

## JIFRESSE: Building a Regional Earth System Model

- greater spatial resolution [O(1-10km)]
- inclusion of more processes and interactions
- closer connections to societal impacts
- a complementary role to GCMs
- a numerical laboratory for GCM parameterization development

## JIFRESSE: Building a Regional Earth System Model

## California Climate Change: Dynamical Downscaling

## California Climate Change: Dynamical Downscaling

**SWE (%)**

**Runoff (%)**

- Hydroclimate Changes: Oct-March; ~2050 vs 1975; 36km

**Runoff**: Up to -80%.   Negatively impacting water resouces in California

**Albedo (%)**

**2m Air Temperature (C)**

**Warming**: 0o to 2.5oC. Larger with altitude.

**Albedo Decreases**: Up to -50%. Implies a snow-albedo impact on temperature signal.

**SWE: **Up to -80%

**Snow physics modeling is important**

**Notes:**
Top: 
The decrease in the seasonal snow-water equivalent (SWE) due to the anthropogenic climate change is as large as 80% of the late 20th century values in the southern Sierra Nevada region during winter.

(b) Bottom:
Associates with the overall decrease in precipitation and SWE, the projected seasonal runoff signals are negative in most of California. The decrease in runoff is most pronounced in the Sierra Nevada region during the winter. The runoff decrease in winter adversely affects the water resources in Califronia.

The projected regional scale climate change signals in the seasonal-mean SWE and runoff (% of the late 20th century value)

## California Climate Change: Dynamical Downscaling

- Impact of Model Resolution/Topography

- SWE is generally less in projected future climate.
- Differences in 12km vs 36km are not due to differences in changes to snowfall.

**No topog**
**this high. **

**Notes:**
Large uncertainties in the projection of the Sierra Nevada SWE can be associated with the horizontal resolution of an RCM. For example, the changes in the winter season SWE ratio in the Sierra Nevada region due to the climate change projected with different horizontal resolution differ noticeably. The corresponding changes in the seasonal snowfall in terms of the ratio between the future and the present-day values are similar in both simulations. Further investigation shows that the winter season snowfall and SWE are systematically underestimated in the 36km run compared to the 12km simulation results. Thus, the differences in the climate change sensitivity of the SWE between the 12km and 36km simulations could originate from the snow-albedo feedback. The smaller snowfall in the 36km run results in smaller SWE and albedo in the Sierra Nevada region. The smaller albedo in turn further reduces SWE in the 36km simulation. This result suggest that the climate change signals in the fields that are mostly determined by the changes in the large-scale circulation such as precipitation are less susceptible to the configuration of RCM simulations; however, model configuration can be a significant source of uncertainties in projecting the climate change signals in the fields such as SWE and snowmelt that are affected strongly by local feedback in addition to the large-scale circulation chagnes.

The projected winter season SWE ratio in the Sierra Nevada region between the mid-21st and the late 20th century periods in the 36km (blue) and 12km (red) simulations

## California Climate Change: Dynamical Downscaling

- Impact of Snow Albedo/Aerosol Deposition: _*Role of Emissions?*_

**SWE sensitivity to changes in snow albedo**

**Notes:**
Changes in snow albedo, possibly by the deposition of anthropogenic BC on the Sierra Nevada snowpack, can alter the SWE variations during the course of a cold season. Notable decrease and increase of SWE in response to the decrease and increase in snow albedo, respectively, occurs in the experiment. The increase in SWE due to increased snow albedo occurs later in the season than the SWE decreases due to the decreased snow albedo. 

## California Climate Change: Dynamical Downscaling

- _Sensitivity_
- _Simulation_
- NCEP/NCAR
- Reanalysis
- 1998

**Forcing**

## California Climate Change: Dynamical Downscaling

- Impact of Snow Layer Physics Representation

- Significant Reductions in modeled SWE biases – typically an over estimate.

- Less realistic single layer snow models may _underestimate _projected snowpack loss.

- 1-Layer Model

- 3-Layer Model

**Notes:**
A comparison of the spring SWE simulated using the single-layer snow model in SSiB-1 (a) and the three-layer version in SSiB-3 (b) shows that the model bias in the single-layer snow model could be reduced by over 50% by using the three-layer snow model.

The results suggest that more physically comprehensive calculation within the context of a multi-layer snow model can be important in improving snowpack simulation, especially during major ablation season.

## California Climate Change: Santa Ana Winds

- Analysis of a regional climate hindcast'indicates Santa Ana wind conditions have decreased 30-50% from 1959 to 2001.
- Reduction arises from both large-scale synoptic forcing (strong offshore upper level winds) and local katabatic forcing (cold desert air pouring through the gaps).
- The climate change dynamic downscaling experiment suggests further decreases in the future (~2050).

- Hughes et al. 2008

## Summary

-  An trend in earlier Sierra snowmelt timing is present in monthly SWE observations - attributed to the sensitivity of peak snow mass date to local March temperature.
-  Regional dynamic downscaling experiments have been performed based on NCAR CCSM SRESA1B suggesting considerable changes to CA hydroclimate by 2050.
-  There is considerable model sensitivity of CA snowmelt and snowpack loss to model resolution, snow albedo treatment, and model snow layer formulation.
- Santa Ana winds are less frequent under climate warming conditions because the continental interior warms more than ocean, altering large-scale and local pressure gradients.
*Caveat**: Some results based on only one GCM projection & one RESM formulation.*

- www.jifresse.ucla.edu

## Future Work

-  Regional model validation with ground-based and satellite observations where possible : synoptic fields (e.g., temperature, clouds, winds), hydroclimate (e.g. snowcover, albedo), air quality.
- Continue work on improving snow physics, e.g., multi-layer formulation, snow spectral albedo parameterization based on snow grain size and black carbon/dust contamination.
-  Compare observational dataset of peak snow mass date to regional model output both for validation purposes and for understanding mechanisms for the changes.
- Santa Ana Winds: 1) Validate analysis against ground-based observations, and  2) Identify how other critical fire weather parameters (e.g., relative humidity) have changed.
- Investigation of the impact of anthropogenic climate change on the air quality in California.

- www.jifresse.ucla.edu