Land Surface Processes in Global Climate Models (2) Land Surface Processes in Global Climate Models (2)

Study water cycle trend using the NCAR Community Land Model (CLM3)

Study water cycle trend using the NCAR Community Land Model (CLM3)

Question: What is the trend of water cycle in the last 50 years?

Model experimentsModel experiments

57 years (1948-2004) of CLM offline simulation Resolution: T42 (~2.8º) The forcing dataset: 3-hrly and T62 (~1.875°) Precipitation, surface air temperature, downward solar

radiation, specific humidity, wind speed and air pressure

• Combined the intramonthly variations from the NCEP/NCAR 6-hrly reanalysis with monthly time series from station records (T, P, CLD)

The validation datasets include streamflow from 921 rivers around the world, continental freshwater discharge, surface runoff and soil moisture

57 years (1948-2004) of CLM offline simulation Resolution: T42 (~2.8º) The forcing dataset: 3-hrly and T62 (~1.875°) Precipitation, surface air temperature, downward solar

radiation, specific humidity, wind speed and air pressure

• Combined the intramonthly variations from the NCEP/NCAR 6-hrly reanalysis with monthly time series from station records (T, P, CLD)

The validation datasets include streamflow from 921 rivers around the world, continental freshwater discharge, surface runoff and soil moisture

Qian, Dai, Trenberth and Oleson (2006), J. Hydrometeor.

Simulated mean annual cycle for the world’s 10 largest rivers: validation using observationSimulated mean annual cycle for the world’s 10 largest rivers: validation using observation

Observation

NCEP unadjusted

NCEP Adjusted

Amazon

Congo

Orinoco

Changjiang

Bahmaputra

Mississippi

Yenisey

Parana

Lena

Mekong

Simulated long-term mean streamflow for the world’s 200 largest rivers: Validation using observation

Simulated long-term mean streamflow for the world’s 200 largest rivers: Validation using observation

Simulated water-year annual mean streamflow for 12 rivers: validation against observation

Simulated water-year annual mean streamflow for 12 rivers: validation against observation

Simulated long-term mean runoff: Validation against Fekete et al. dataSimulated long-term mean runoff:

Validation against Fekete et al. data

Qian, Dai, Trenberth and Oleson (2006), J. Hydrometeor.

Comparison of long-term mean freshwater discharge into the global oceans

Comparison of long-term mean freshwater discharge into the global oceans

Comparison of soil moisture: CLM3 vs measurements at Illinois, U.S.

Comparison of soil moisture: CLM3 vs measurements at Illinois, U.S.

Summary of global simulation using CLM3Summary of global simulation using CLM3 The CLM3 reproduces many aspects of the long-term mean, annual cycle,

interannual and decadal variations, and trends of streamflow for many large rivers (e.g., the Orinoco, Changjiang, Mississippi, etc.), although substantial biases exist.

The simulated long-term-mean freshwater discharge into the global and individual oceans is comparable to 921 river-based observational estimates.

Observed soil moisture variations over Illinois and parts of Eurasia are generally simulated well, with the dominant influence coming from precipitation.

It is also shown that unrealistically low intensity and high frequency of precipitation in original NCEP reanalysis result in too much evaporation and too little runoff, which leads to lower than observed river flows. This problem can be reduced by adjusting the precipitation rates using observed precipitation-frequency maps.

The results suggest that the CLM3 simulations are useful for climate change analysis.

The CLM3 reproduces many aspects of the long-term mean, annual cycle, interannual and decadal variations, and trends of streamflow for many large rivers (e.g., the Orinoco, Changjiang, Mississippi, etc.), although substantial biases exist.

The simulated long-term-mean freshwater discharge into the global and individual oceans is comparable to 921 river-based observational estimates.

Observed soil moisture variations over Illinois and parts of Eurasia are generally simulated well, with the dominant influence coming from precipitation.

It is also shown that unrealistically low intensity and high frequency of precipitation in original NCEP reanalysis result in too much evaporation and too little runoff, which leads to lower than observed river flows. This problem can be reduced by adjusting the precipitation rates using observed precipitation-frequency maps.

The results suggest that the CLM3 simulations are useful for climate change analysis.

The evaporation trend in the Mississippi River basinThe evaporation trend in the Mississippi River basin

Previous studies: Incomplete observations lead to conflicting estimates of E trend

(1) Energy balance: Cloud is increasing, Fsw is decreasing, Pan evaporation (Epan) is decreasing

Peterson et al. (1995, Nature): E is decreasing Brutsaert & Parlange (1998, Nature) and Golubev et al. (2001, GRL):

E is negatively correlated with Epan, so E is increasing

Roderick and Farquhar (2002, Science): E is negatively correlated with Epan only under specific conditions, not in general. So E is decreasing

(2) Water balance: P is increasing, R is increasing, P-R is increasing Milly & Dunne (2001, GRL); Walter et al. (2004, J. Hydrometeor.): E is increasing

Previous studies: Incomplete observations lead to conflicting estimates of E trend

(1) Energy balance: Cloud is increasing, Fsw is decreasing, Pan evaporation (Epan) is decreasing

Peterson et al. (1995, Nature): E is decreasing Brutsaert & Parlange (1998, Nature) and Golubev et al. (2001, GRL):

E is negatively correlated with Epan, so E is increasing

Roderick and Farquhar (2002, Science): E is negatively correlated with Epan only under specific conditions, not in general. So E is decreasing

(2) Water balance: P is increasing, R is increasing, P-R is increasing Milly & Dunne (2001, GRL); Walter et al. (2004, J. Hydrometeor.): E is increasing

Water balance

Energy balance

Fsw LHFlw SH

E participates in two balances at the land surface

dS/dt

P E

RG

Questions:Questions:

Has ET increased or decreased?

Can we satisfy BOTH the heat and water budgets?

Our study: Complete evaluation of these two budgets using observation-constrained global land model simulations

Has ET increased or decreased?

Can we satisfy BOTH the heat and water budgets?

Our study: Complete evaluation of these two budgets using observation-constrained global land model simulations

Qian, Dai, and Trenberth (2007), J. Climate

Basin-averaged energy budgetBasin-averaged energy budget

Basin-averaged water budgetBasin-averaged water budget

Model sensitivity experiments on factors affecting E trend: dominated by precipitation change

Model sensitivity experiments on factors affecting E trend: dominated by precipitation change

Precip Runoff

Evap Storage

Trend map of water budgetTrend map of water budget

Qian, Dai, and Trenberth (2007), J. Climate

SW LH

LW SH

Trend map of energy budgetTrend map of energy budget

Fsw LHFlw SH

dS/dt

P E

RG

Both energy balance and water balance support that evaporation is increasing, and the water cycle is intensified during the last 50 years!

Summary: Water cycle trend of Mississippi River basin

Summary: Water cycle trend of Mississippi River basin

Energy budget Water budget