Coupling Strength between Soil Moisture and Precipitation Tunings and the Land-Surface Database Ecoclimap Experiment design: Two 10-member ensembles -

Slides:



Advertisements
Similar presentations
Regional climate change over southern South America: evolution of mean climate and extreme events Silvina A. Solman CIMA (CONICET-UBA) Buenos Aires ARGENTINA.
Advertisements

Detection of a direct carbon dioxide effect in continental river runoff records N. Gedney, P. M. Cox, R. A. Betts, O. Boucher, C. Huntingford & P. A. Stott.
American Monsoons-ENSO teleconnection Vasu Misra, Dept. of Earth, Ocean and Atmospheric Science, Florida State University 1.
How do model errors and localization approaches affects model parameter estimation Juan Ruiz, Takemasa Miyoshi and Masaru Kunii
Pan American Land Feedbacks on Precipitation Robert E. Dickinson (Gatech) Acknowledging contributions from Rong Fu (Gatech), and Guiling Wang (U Conn.)
Jiangfeng Wei with support from Paul Dirmeyer, Zhichang Guo, and Li Zhang Center for Ocean-Land-Atmosphere Studies Maryland, USA.
Interannual Variability in Summer Hydroclimate over North America in CAM2.0 and NSIPP AMIP Simulations By Alfredo Ruiz–Barradas 1, and Sumant Nigam University.
World Geography Unit 2: World Climate Patterns Ocean Currents and Other Factors That Affect Climate.
AMMA-UK WP3 – Convection and dynamics Doug Parker Institute for Atmospheric Science School of Earth and Environment University of Leeds 29 November 2004.
Soil and the Hydrologic Cycle Read Ch 6 Brady and Weil Quiz 6 on Monday, Oct. 15.
Delayed onset of the South American Monsoon during the Last Glacial Maximum Kerry H. Cook and Edward K. Vizy, Cornell University I. INTRODUCTION Climate.
Relationships between wind speed, humidity and precipitating shallow cumulus convection Louise Nuijens and Bjorn Stevens* UCLA - Department of Atmospheric.
On the simulation of regional climate in South America with emphasis on extremes and surface processes Claudio Menéndez, Andrea Carril, Anna Sörensson,
What causes Climate ? Text Book page #
Summary The CLASS U3M 1D (Unsaturated Moisture Movement Model) was used to simulate water content of 4 soil levels at Diamante, Entre Rios. Hydraulic parameters.
CSIRO LAND and WATER Estimation of Spatial Actual Evapotranspiration to Close Water Balance in Irrigation Systems 1- Key Research Issues 2- Evapotranspiration.
Institute of Meteorology and Water Management – NRI Extensive tests of lower-boundary-variation-based COSMO EPS COTEKINO Priority Project -
Relationship between Antecedent Land Surface Conditions and Precipitation in the North American Monsoon Region Chunmei Zhu a, Dennis P. Lettenmaier a,
Regional Climate Modeling in the Source Region of Yellow River with complex topography using the RegCM3: Model validation Pinhong Hui, Jianping Tang School.
THE INDIAN OCEAN DIPOLE AND THE SOUTH AMERICAN MONSOON SYSTEM Anita Drumond and Tércio Ambrizzi University of São Paulo São Paulo, 2007
Understanding physical processes linked to climate variability and change in the South America Monsoon System Carolina Vera 1, C. Junquas 1,2, H. Le Treut.
Climatic Zones p P. 75 fig. 5.1.
International CLIVAR Working Group for Seasonal-to- Interannual Prediction (WGSIP) Ben Kirtman (Co-Chair WGSIP) George Mason University Center for Ocean-Land-Atmosphere.
Recent Analyses of Drought Character and Prediction Randal Koster, GMAO, NASA/GSFC (with help from numerous colleagues: Sarith Mahanama, Greg Walker, Siegfried.
INDIA and INDO-CHINA India and Indo-China are other areas where the theoretical predictability using the interactive soil moisture is superior to the fixed.
Changes and Feedbacks of Land-use and Land-cover under Global Change Mingjie Shi Physical Climatology Course, 387H The University of Texas at Austin, Austin,
NERC Centre for Global Atmospheric Modelling Department of Meteorology, University of Reading The role of the land surface in the climate and variability.
From Climate Data to Adaptation Large-ensemble GCM Information and an Operational Policy-Support Model Mark New Ana Lopez, Fai Fung, Milena Cuellar Funded.
EGU General Assembly C. Cassardo 1, M. Galli 1, N. Vela 1 and S. K. Park 2,3 1 Department of General Physics, University of Torino, Italy 2 Department.
Objectives –climatology –climate –normal Vocabulary –tropics –temperate zone –polar zone Recognize limits associated with the use of normals. Explain.
Characterization of the Global Hydrologic Cycle from a Back-Trajectory Analysis of Atmospheric Water Vapor Paul A. Dirmeyer Kaye L. Brubaker 04 / 15 /
Coupling of the Common Land Model (CLM) to RegCM in a Simulation over East Asia Allison Steiner, Bill Chameides, Bob Dickinson Georgia Institute of Technology.
How are Land Properties in a Climate Model Coupled through the Boundary Layer to Affect the Amazon Hydrological Cycle? Robert Earl Dickinson, Georgia Institute.
Building Asian Climate Change Scenarios by Multi-Regional Climate Models Ensemble S. Wang, D. Lee, J. McGregor, W. Gutowski, K. Dairaku, X. Gao, S. Hong,
How much do different land models matter for climate simulation? Jiangfeng Wei with support from Paul Dirmeyer, Zhichang Guo, Li Zhang, Vasu Misra, and.
Two characteristics of Climate that are most important: 1) The average temperature over the year 2) The annual temperature range (difference between the.
The Role of Antecedent Soil Moisture on Variability of the North American Monsoon System Chunmei Zhu a, Yun Qian b, Ruby Leung b, David Gochis c, Tereza.
Institute of Hydrology Slovak Academy of Sciences Katarína Stehlová 6 th ALPS-ADRIA SCIENTIFIC WORKSHOP 30 April - 5 May, 2007 Obervellach, Austria Assessment.
Scaling and Analysis of Long Time Series of Soil Moisture Content By Gabriel Katul Nicholas School of the Environment and Earth Sciences, Duke University.
Part I: Representation of the Effects of Sub- grid Scale Topography and Landuse on the Simulation of Surface Climate and Hydrology Part II: The Effects.
Regional Climate Modeling Simulations of the West African Climate System Gregory S. Jenkins, Amadou Gaye, Bamba Sylla LPASF AF20.
Introduction to and validation of MM5/VIC modeling system.
AGRICULTURAL DROUGHT INDICATORS AT REGIONAL SCALE BASED ON MODELS OF WATER BALANCE AT LEFT MARGIN OF GUADIANA RIVER N. Kotsovinos, P. Angelidis Democritus.
SeaWiFS Highlights April 2002 SeaWiFS Views Bright Water in the Rio de la Plata of South America Gene Feldman, NASA GSFC, Laboratory for Hydrospheric Processes,
Local forcing and intra-seasonal modulation of the South America summer monsoon: Soil moisture, SST and topography Alice Grimm Dept. of Physics - Federal.
Use of a high-resolution cloud climate data set for validation of Rossby Centre climate simulations Presentation at the EUMETSAT Meteorological Satellite.
© Crown copyright Met Office Uncertainties in the Development of Climate Scenarios Climate Data Analysis for Crop Modelling workshop Kasetsart University,
Role of Soil Moisture Coupling on the Surface Temperature Variability Over the Indian Subcontinent J. Sanjay M.V.S Rama Rao and R. Krishnan Centre for.
Relationship between Antecedent Land Surface Conditions and Warm Season Precipitation in the North American Monsoon Region Chunmei Zhu a, Dennis P. Lettenmaier.
APPLICATION OF A SOIL WATER BALANCE MODEL TO THE MERCOSUR AREA. J. Tomasella, J.A. Marengo M. Doyle and G. Coronel MAR DEL PLATA OCTOBER 2002.
1 Xiaoyan Jiang, Guo-Yue Niu and Zong-Liang Yang The Jackson School of Geosciences The University of Texas at Austin 03/20/2007 Feedback between the atmosphere,
Ongoing Work As part of a project intended to evaluate the potential for improving water resources management in Mexico through use of climate forecasts,
Climatology of the Río de la Plata Basin: short and long term variability Mario Bidegain Facultad de Ciencias Universidad de la Republica Uruguay Workshop.
NAME SWG th Annual NOAA Climate Diagnostics and Prediction Workshop State College, Pennsylvania Oct. 28, 2005.
Conclusions: ● The spring land condition in the SW U.S. has a memory of winter precipitation anomalies, and the spring land memory in this area seems to.
Air Masses and ITCZ. Topic 4: Air Masses and ITCZ Global wind circulation and ocean currents are important in determining climate patterns. These are.
The effect of increased entrainment on monsoon precipitation biases in a GCM Stephanie Bush (University of Reading/UK Met Office), Andrew Turner (Reading),
1 Role of Antecedent Land Surface Conditions on North American Monsoon Rainfall Variability Chunmei Zhu Department of Civil and Environmental Engineering.
Earth Science Chapter 8 Climates.
Coupled crop-climate modelling
ALADIN / HIRLAM 19th Workshop / All-Staff Meeting Utrecht, May 2009
The Water Budget.
Validation of GCM, and the need of High resolution atmospheric and hydrological model Vicente Barros and Mariano Re San José de Costa Rica 28 May 2003.
Central American collaborative interests in NAME
Alfredo Ruiz-Barradas Sumant Nigam
Silvina A. Solman CIMA (CONICET-UBA) DCAO (FCEN-UBA)
Analysis of influencing factors on Budyko parameter and the application of Budyko framework in future runoff change projection EGU Weiguang Wang.
CENTRO DE INVESTIGACIONES DEL MAR Y LA ATMÓSFERA
20th Century Sahel Rainfall Variability in IPCC Model Simulations and Future Projection Mingfang Ting With Yochanan Kushnir, Richard Seager, Cuihua Li,
The Tropical Monsoon Aims: to investigate the causes and characteristics of the tropical monsoon.
Presentation transcript:

Coupling Strength between Soil Moisture and Precipitation Tunings and the Land-Surface Database Ecoclimap Experiment design: Two 10-member ensembles - Period November 1992 – March 1993 Ensemble W: the soil moisture is calculated by the model at each time step - the soil is interactive with the atmosphere Ensemble S: All ensemble members are forced, at each time step, to maintain the same space-time varying series of soil moisture. The soil moisture field is a boundary condition for the atmosphere - the atmosphere does not feed back upon the soil moisture. Coupling Strength CS: Since soil moisture is a boundary condition for ensemble S but not for ensemble W, the difference Ω(S) – Ω(W) isolates the fraction of atmospheric variability that is explained by the soil moisture and is used as a measure of the coupling strength. Similarity parameter Ω v : Variance of the mean time series of all ensemble members ensemble inter- member variance Number of ensemble members Ω is the ratio of the variance of the variable v that is explained by (all) boundary conditions in relation to total variance. Results: We present the coupling strength between soil moisture and evaporation and soil moisture and precipitation. The precipitation coupling strength depends to some (unknown) degree on the evapotranspiration coupling strength but also on e.g. model parameterizations of boundary layer and moist convection. The precipitation coupling strength is proposed by various authors (e.g. GLACE project) to be highest in transition zones – regions that are neither arid nor humid. SWA Evaporation coupling strength binned according to Soil Water Availability (SWA) CS In arid regions the atmosphere is dry and rainfall easily evaporates to the atmosphere. High coupling strength “HOT SPOTS” Coupling Strength Soil Moisture – Evapotranspiration January -93 Coupling Strength Soil Moisture – Precipitation January -93 SWA Precipitation coupling strength binned according to Soil Water Availability (SWA) CS In transition zones, the coupling to evapotranspiration is intermediate AND the atmosphere can get unstable by a less amount of added water vapor. Higher coupling strength In humid regions, the air is wet and the soil is close to field capacity, and 1. rainfall will not change the soil moisture to such a high degree. 2. The evapotranspiration will be limited by the wet atmosphere Low coupling strength In arid regions the atmosphere is too dry to get unstable. Lower coupling strength t t Initialization dates SOIL MOISTURE ENSEMBLE S SOIL MOISTURE ENSEMBLE W Annual cycle of Precipitation, Amazon region Annual cycle of T2m, Amazon region Annual cycle of Precipitation, La Plata Basin To increase the RCA3 performance in simulating the South American climate, the land-surface database Ecoclimap was incorporated and a set of tunings were performed. The monsoon precipitation was improved for the Amazon and Plata Basin regions although large negative winter bias prevails. Anna A. Sörensson (1), Claudio G. Menéndez (1), Ulf Hansson (2), Patrick Samuelsson (2), Ulrika Willén (2) (1) Centro de Investigaciones del Mar y la Atmósfera, CONICET/UBA, Buenos Aires, Argentina (2) Rossby Centre, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden Anna A. Sörensson (1), Claudio G. Menéndez (1), Ulf Hansson (2), Patrick Samuelsson (2), Ulrika Willén (2) (1) Centro de Investigaciones del Mar y la Atmósfera, CONICET/UBA, Buenos Aires, Argentina (2) Rossby Centre, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden Soil Moisture - Atmosphere Coupling in the Rossby Centre Regional Atmospheric Model during the South American Monsoon Soil Moisture - Atmosphere Coupling in the Rossby Centre Regional Atmospheric Model during the South American Monsoon Initial Soil Moisture – the effect of a dry/wet winter on SAMS Initial soil moisture of ensemble “DRY” Initial soil moisture of ensemble “WET” Sm(x i,y j ) The soil moisture memory could influence on the intraseasonal variability of precipitation during the development of the South American Monsoon System (SAMS) and potentially contributes to atmospheric variability and seasonal predictability. We explore the interaction between soil moisture and atmosphere during the SAMS of through a) calculating the coupling strength and b) studying the effect of initial dry and wet soil moisture conditions, using the Rossby Centre regional atmospheric climate model (RCA3). The model has been adapted to the South American region through a series of tunings and by incorporating the surface database Ecoclimap. Introduction We explored the influence of anomalous soil moisture initial conditions on the intraseasonal development of the SAMS on a monthly timescale. Two ensembles of five members each were realized, one with anomalously dry and the other with anomalously wet land surface initial conditions over the whole domain. The simulated period is August 1992 – March PrecipitationWinds and temperature 850hPa The choice of land surface database and parameters like soil depth and leaf area index is important for the for the performance of RCA3 over South America. With the database Ecoclimap and a set of tunings to the atmosphere, the surface temperature and the summer precipitation was improved for important South American regions, including La Plata Basin. La Plata Basin seems to be a region where the precipitation is partly controlled by the soil moisture in January. Results were similar for other months. The coupling strength of evapotanspiration is very high for la Plata Region, which indicates that the soil probably is too dry in RCA3 in this region, perhaps due to the winter precipitation deficit. A very dry winter with a very dry soil in August, induced continental scale circulation changes through changed Bowen Ratio and deep convective areas. Moisture fluxes from the Atlantic increased and initiated the monsoon earlier than for a simulation with wet initial conditions. Conclusions The spring T2m bias of Amazon region was removed by Ecoclimap.