Figure 1: Top) Ln(Chl) anomaly (units are % difference from monthly mean) and Bottom) SST anomaly for 2010 (units are C). Anomalies are calculated from.

Slides:

Advertisements

Similar presentations

Spatial and Temporal Variability of GPCP Precipitation Estimates By C. F. Ropelewski Summarized from the generous input Provided by G. Huffman, R. Adler,

Advertisements

Objectives (BPS chapter 24)

INTERDECADAL OSCILLATIONS OF THE SOUTH AMERICAN MONSOON AND THEIR RELATIONSHIP WITH SEA SURFACE TEMPERATURE João Paulo Jankowski Saboia Alice Marlene Grimm.

Climate Variability and Prediction in the Little Colorado River Basin Matt Switanek 1 1 Department of Hydrology and Water Resources University of Arizona.

Principles of Sea Level Measurement Long-term tide gauge records  What is a tide station?  How is sea level measured relative to the land?  What types.

Scientific Notation A short-hand way of writing large numbers without

Focus on High Latitudes State of the Antarctic & Southern Ocean Climate System Authors: P. A. Mayewski, M. P. Meredith, C. P. Summerhayes, J. Turner, A.

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Satellite Observations of Seasonal Sediment Plume in the Central East China.

Lecture 5 Correlation and Regression

SIO 210: ENSO conclusion Dec. 2, 2004 Interannual variability (end of this lecture + next) –Tropical Pacific: El Nino/Southern Oscillation –Southern Ocean.

Group Meeting 2010/03/30 R Kirsten Feng. Nutrient and salinity decadal variations in the central and eastern North Pacific E. Di Lorenzo, J. Fiechter,

Oceanographic Patterns in ECCO & Satellite Imagery with Applications to Fisheries Li Luo and Dale Kiefer 11/01/2012.

Green River Basin  New Verification Tool  7 Forecast Points Selected  Five Major Inquires William B. Reed Green River Basin November 2008.

El Niño-Southern Oscillation in Tropical Column Ozone and A 3.5-year signal in Mid-Latitude Column Ozone Jingqian Wang, 1* Steven Pawson, 2 Baijun Tian,

Cambiamento attuale: osservazioni CLIMATOLOGIA Prof. Carlo Bisci.

Orbit Characteristics and View Angle Effects on the Global Cloud Field

Linear Regression Least Squares Method: the Meaning of r 2.

The climate and climate variability of the wind power resource in the Great Lakes region of the United States Sharon Zhong 1 *, Xiuping Li 1, Xindi Bian.

NASA Ocean Color Research Team Meeting, Silver Spring, Maryland 5-7 May 2014 II. Objectives Establish a high-quality long-term observational time series.

REGRESSION DIAGNOSTICS Fall 2013 Dec 12/13. WHY REGRESSION DIAGNOSTICS? The validity of a regression model is based on a set of assumptions. Violation.

Time Series A collection of measurements recorded at specific time intervals.

Lesson 6.1 AIM: Understanding Multiplication of Exponents.

Anomalies from the monthly mean climatology: Black: actual temperatures Green: climatology Anomalies m depends on the month.

Herbicides in Metro Atlanta Streams and Rivers Data Analysis Cristal Moon.

1. Introduction 2. The model and experimental design 3. Space-time structure of systematic error 4. Space-time structure of forecast error 5. Error growth.

Example x y We wish to check for a non zero correlation.

The CFS ensemble mean (heavy blue line) predicts La Nina will last through at least the Northern Hemisphere spring

Indo-Pacific Sea Surface Temperature Influences on Failed Consecutive Rainy Seasons over Eastern Africa** Andy Hoell 1 and Chris Funk 1,2 Contact:

Basic statistical concepts and techniques Mean and variance Probability distribution, and statistical significance Harmonic analysis and power spectrum.

Scientific Notation & Significant Figures. Accuracy and Precision Review Precision- how close measurements are to each other (range) Accuracy- how close.

Intercomparison of satellite retrieved aerosol optical depth over ocean G. Myhre, F. Stordal, M. Johnsrud, A. Ignatov, M.I. Mishchenko, I.V. Geogdzhayev,

Orbit comparison for ERS-2 mission between GFZ and REAPER The GFZ orbit is referred to as GFZ in the following study The REAPER orbit is referred to as.

New Aerosol Models for Ocean Color Retrievals Zia Ahmad NASA-Ocean Biology Processing Group (OBPG) MODIS Meeting May 18-20, 2011.

Oceanography 569 Oceanographic Data Analysis Laboratory Kathie Kelly Applied Physics Laboratory 515 Ben Hall IR Bldg class web site: faculty.washington.edu/kellyapl/classes/ocean569_.

ENSO Influence on Atlantic Hurricanes via Tropospheric Warming Brian Tang* and David Neelin Dept. of Atmospheric and Oceanic Sciences, UCLA Institute of.

Four files erik_a2_stockholm_temp Erik simulation scenario A2 until 2100 erik_a2_stockholm_prec Erik simulation scenario A2 until.

MODIS Atmosphere Products: The Importance of Record Quality and Length in Quantifying Trends and Correlations S. Platnick 1, N. Amarasinghe 1,2, P. Hubanks.

Pearson’s Correlation The Pearson correlation coefficient is the most widely used for summarizing the relation ship between two variables that have a straight.

Decadal Variability in the Southern Hemisphere Xiaojun Yuan 1 and Emmi Yonekura 2 1 Lamont-Doherty Earth Observatory Columbia University 2 Department Environment.

Incorporating Satellite Time-Series data into Modeling Watson Gregg NASA/GSFC/Global Modeling and Assimilation Office Topics: Models, Satellite, and In.

Examining the connection between the dynamics of western boundary shelves and the deep sea using satellite altimetry data Nicholas Trefonides and James.

Module 1 Day 3 Power Properties.

From: Visual speed sensitivity in the drum corps color guard

Correlation and Regression

Fundamentals Data processing concepts

Warmup Solve –2x2 + 5x = 0. Approximate non-integral answers. A. 0

Linear Regression Models

El Nino Upwelling and Ocean Productivity

Theme 7 Correlation.

ATMS790: Graduate Seminar, Yuta Tomii

NSAF and GeneChip datasets have similar PLGEM parameters.

A Source for Feature-Based Attention in the Prefrontal Cortex

Michael Erickson’s Quasi-awesome Expert* Winter Forecast**

Least Squares Method: the Meaning of r2

Land Performance Analysis for the Sahel

Fig. 1 The temporal correlation coefficient (TCC) skill for one-month lead DJF prediction of 2m air temperature obtained from 13 coupled models and.

Draw the balance scales shown below on a blank page after Page 105.

Volume 55, Issue 3, Pages (August 2007)

Saraju K. Baidya Department of Hydrology and Meteorology Nepal

Change in bone area does not correlate with cartilage loss over 12 months in individuals with knee OA: Data from the osteoarthritis initiative M.A. Bowes,

Globale Mitteltemperatur

Hippocampal “Time Cells”: Time versus Path Integration

Globale Mitteltemperatur

Describe the similarities and differences of the top figure and the bottom figure shown to the right.

Volume 25, Issue 5, Pages (March 2015)

AP Human Geography Population Pyramids.

Figure 2 Atlantic sector of the first rotated EOF of non-ENSO global SST variability for 1870–2000 referred to as the “Atlantic multidecadal mode” (38,

The Effect of ENSO on Precipitation in Atlanta

Fig. 2 Year-to-year changes in the number of tornadoes, low-level jet, and moisture flux convergence over the SGP. Year-to-year changes in the number of.

Globale Mitteltemperatur

Presentation transcript:

Figure 1: Top) Ln(Chl) anomaly (units are % difference from monthly mean) and Bottom) SST anomaly for 2010 (units are C). Anomalies are calculated from the long-term record is really Dec 1, 2009 to Nov 30, SeaWiFS ceased operating on Dec. 14, 2010.

SST<15C (NH) SST >15C SST<15C (SH) Figure 2: Time series of log(Chl) (Green) and SST (Blue) for ocean regions delineated by mean SST values > or < than 15C. Values are standardized (unit variance and zero mean)

Figure 3: Top) Spatial distribution of the correlation coefficient (R) between log(Chl) and MEI and Bottom) the time trend in log(Chl) over the entire SeaWiFS record. Only significant (95% c.i.) correlations and trends are plotted. SeaWiFS operated from Oct to Dec