Michiko Masutani

Teleconnective Response of the Pacific–North American Region Atmosphere to Large Central Equatorial Pacific SST Anomalies

Abstract A prominent year-round ensemble response to a global sea surface temperature (SST) anomaly field fixed to that for January 1992 (near the peak of a major warm El Nino–Southern Oscillation episode) was observed in a 20-yr integration of the general circulation model used for operational seasonal prediction by the U.S. National Weather Service. This motivated a detailed observational reassessment of the teleconnections between strong SST anomalies in the central equatorial Pacific Ocean and Pacific–North America region 700-hPa heights and U.S. surface temperatures and precipitation. The approach used consisted of formation of monthly mean composites formed separately from cases in which the SST anomaly in a key area of the central equatorial Pacific Ocean was either large and positive or large and negative. Extensive permutation tests were conducted to test null hypotheses of no signal in these composites. The results provided a substantial case for the presence of teleconnections to either the pos...

SST-Forced Seasonal Simulation and Prediction Skill for Versions of the NCEP/MRF Model

The feasibility of using a two-tier approach to provide guidance to operational long-lead seasonal prediction explored. The approach includes a first forecast of global sea surface temperature (SSTs) using a coupled general circulation model, followed by an atmospheric forecast using an atmospheric general circulation model (AGCM). For this exploration, ensembles of decade-long integrations of the AGCM driven by observed SSTs and ensembles of integrations of selects cases driven by forecast SSTs have been conducted. The ability of the model in these sets of runs to reproduce observed atmospheric conditions has been evaluated with a multiparameter performance analysis. Results have identified performance and skill levels in the specified SST runs, for winters and springs over the Pacific/North America region, that are sufficient to impact operational seasonal predictions in years with major El Nino Southern Oscillation (ENSO) episodes. Further, these levels were substantially reproduced in the forecast SST runs for 1-month leads and in many instances for up to one season leads. In fact, overall the 0- and 1-month-lead forecasts of better than corresponding official forecasts. Thus, there is considerable reason to develop a dynamical component for the official seasonal forecast process. 23 refs., 10 figs., 3 tabs.

LIDAR-MEASURED WIND PROFILES The Missing Link in the Global Observing System

The three-dimensional global wind field is the most important remaining measurement needed to accurately assess the dynamics of the atmosphere. Wind information in the tropics, high latitudes, and stratosphere is particularly deficient. Furthermore, only a small fraction of the atmosphere is sampled in terms of wind profiles. This limits our ability to optimally specify initial conditions for numerical weather prediction (NWP) models and our understanding of several key climate change issues. Because of its extensive wind measurement heritage (since 1968) and especially the rapid recent technology advances, Doppler lidar has reached a level of maturity required for a space-based mission. The European Space Agency (ESA)s Atmospheric Dynamics Mission Aeolus (ADM-Aeolus) Doppler wind lidar (DWL), now scheduled for launch in 2015, will be a major milestone. This paper reviews the expected impact of DWL measurements on NWP and climate research, measurement concepts, and the recent advances in technology that ...

Observing System Simulation Experiments

Observing System Simulation Experiments (OSSEs) are typically designed to use data assimilation ideas (see chapter Mathematical Concepts in Data Assimilation, Nichols) to investigate the potential impacts of prospective observing systems (observation types and deployments). They may also be used to investigate current observational and data assimilation systems by testing the impact of new observations on them. The information obtained from OSSEs is generally difficult, or in some contexts impossible, to obtain in any other way.

Impact of Different Satellite Wind Lidar Telescope Configurations on NCEP GFS Forecast Skill in Observing System Simulation Experiments

AbstractThe Global Wind Observing Sounder (GWOS) concept, which has been developed as a hypothetical space-based hybrid wind lidar system by NASA in response to the 2007 National Research Council (NRC) decadal survey, is expected to provide global wind profile observations with high vertical resolution, precision, and accuracy when realized. The assimilation of Doppler wind lidar (DWL) observations anticipated from the GWOS is being conducted as a series of observing system simulation experiments (OSSEs) at the Joint Center for Satellite Data Assimilation (JCSDA). A companion paper (Riishojgaard et al.) describes the simulation of this lidar wind data and evaluates the impact on global numerical weather prediction (NWP) of the baseline GWOS using a four-telescope configuration to provide independent line-of-sight wind speeds, while this paper sets out to assess the NWP impact of GWOS equipped with alternative paired configurations of telescopes. The National Centers for Environmental Prediction (NCEP) Gri...

Dynamical Mechanisms of the 1995 California Floods

Abstract The link between El Nino and the California wintertime rainfall has been reported in various studies. During the winter of 1994/95, warm sea surface temperature anomalies (SSTAs) were observed in the central Pacific, and widespread significant flooding occurred in California during January 1995 and March 1995. However, the El Nino–Southern Oscillation alone cannot explain the flooding. In March 1995 California suffered flooding after the warm SSTA over the central Pacific had weakened considerably. During November and December, in spite of El Nino conditions, California was not flooded, and more than two standard deviations above normal SSTA in the North Pacific were observed. A possible link between midlatitude warm SSTA and the timing of the onset of flooding is suspected within the seasonal forecasting community. The climate condition during the northern winter of 1994/95 is described using the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis da...

Community Global Observing System Simulation Experiment (OSSE) Package (CGOP): Description and Usage

AbstractA modular extensible framework for conducting observing system simulation experiments (OSSEs) has been developed with the goals of 1) supporting decision-makers with quantitative assessments of proposed observing systems investments, 2) supporting readiness for new sensors, 3) enhancing collaboration across the community by making the most up-to-date OSSE components accessible, and 4) advancing the theory and practical application of OSSEs. This first implementation, the Community Global OSSE Package (CGOP), is for short- to medium-range global numerical weather prediction applications. The CGOP is based on a new mesoscale global nature run produced by NASA using the 7-km cubed sphere version of the Goddard Earth Observing System, version 5 (GEOS-5), atmospheric general circulation model and the January 2015 operational version of the NOAA global data assimilation (DA) system. CGOP includes procedures to simulate the full suite of observing systems used operationally in the global DA system, inclu...

Observing system simulation experiments at Joint Center for Satellite Data Assimilation

Observing System Simulation Experiments (OSSEs) are a powerful tool used to assess the potential impact on numerical weather prediction skill from planned or hypothetical future observing systems. Over the last several years an international Joint OSSE collaboration has emerged centered on the use of NASAs and NOAAs data assimilation systems. A Nature Run provided by the European Centre for Medium Range Weather Forecasts (ECMWF) has undergone extensive validation, and a set of simulated reference observations have been subjected to a set of calibration experiments. One of the first candidate observing systems assessed by this system is a wind lidar based on the Global Wind Observing Sounder (GWOS) concept developed by NASA in response to the National Research Council (NRC) Decadal Survey. OSSEs were conducted at Joint Center for Satellite Data Assimilation (JCSDA) and positive impacts from GWOS on medium range weather forecast were demonstrated. For OSSEs, all major observations used for the data assimilation have to be simulated as a control observation in addition to the observations being tested by an OSSE. Simulation of control observations and OSSE calibration are the most significant initial investments for an OSSE before it can be used to evaluate the data impact of future instruments. The Nature Run data and control observation that were simulated at NOAA from the Nature Run are made available from a NASA portal and NCAR for international collaborative Joint OSSEs. Recent developments and plans for a JCSDA OSSE based on a 2012 observation system will be also described.

Analysis and evaluation of Observing System Simulation Experiments (OSSEs) forecast data for Indian summer monsoon

An attempt is made here to evaluate the skill of forecast during boreal summer monsoon regime over the Indian region using the Observation Simulation System Experiment (OSSE) with Doppler Wind LIDAR (DWL) onboard International Space Station (ISS), assimilated in the initial condition. Through various techniques such as pattern correlation, root mean square error etc, we found that there is some positive impact of assimilating the DWL data on the forecast particularly at the lower tropospheric level. Impact on lowering the RMSE is seen for wind fields in the 850 and 500 hPa over Indian domain but not much impact is seen over larger domain. The moisture field and cloud also show marginal impact due to assimilation of DWL. This indicates that possibly due to lower spatial resolution of DWL data and more data gap over Indian and surrounding oceanic region, the impact on forecast is less. However, it shows the promise that monsoon being a convectively coupled system; increase in spatial data by DWL may better resolve the low level wind and subsequently the low level shear which is important for convection trigger in boundary layer.