# Presentation: 092672

## R&D Needs Update

|  | Objects |     Basic Research                  
 (Hypotheses and Understanding) | Applied Research              (Applications and Tools) |
| --- | --- | --- | --- |
|  |    AO/NAOA10      (subseasonal to decadal time scales) | Explore predictability and the impact of ocean-land-atmosphere-ice coupling | Relationship between the wintertime NAO and Atlantic SST anomalies in mid-latitudes and tropics 
Develop tools to predict winter and spring season temperature and snow cover anomalies |
|  | MJOA11 | Explore predictability and the impact of ocean-atmosphere coupling | Empirical wave propagation forecasts for MJO (web outlet same for GFS)
Empirical prediction system for MJO-related impacts on precipitation and surface temperature at Week 2-4 |
|  | Joint effects of ENSO and SST anomalies in different ocean basins | Refine understanding the predictability in association with ENSO
Changing ENSO teleconnection spatial and temporal patterns over time | Develop tools for prediction of US drought using information of Indian Ocean and tropical Pacific SST anomalies  |
|  | Interdecadal and long-term trends (both natural and man-made) |   Assess the state of long-term trends in real-time
  Connection of global trends and US trends
  Joint effects of El Nino and long-term trends | Make application as forecast tools |
|  | Land surface impact | Local and non-local impacts of soil moisture and snow cover on subsequent temperature and precipitation
Theoretical study on unstable modes in the coupled land-atmosphere system | Make application as forecast tools
Apply the theory of unstable modes in the coupled land-atmosphere system to explain persistent drought/flood as nature ‘cycles’ |

**Predictability Studies**

**- A7.1 -**

## R&D Needs Update

|  | Objects |     Basic Research                  
 (Hypotheses and Understanding) | Applied Research         (Applications and Tools) |
| --- | --- | --- | --- |
|  | North American monsoon system | Understand key physical processes and explore predictability of warm season precipitation over the region 
Low level circulation
Moisture sources (GOC-vs-GOM), transport and budget
Diurnal cycle
Double peak structure 
Dynamical linkages (relationship between precipitation variability in the SW and Great Plains; interactions between tropical easterly waves and mid-latitude westerly waves)
Extreme events 
Role of land surface (soil moisture, snow, vegetation)
Role of remote-vs-local SST’s anomalies (ENSO, PDO, TAV)
Role of MJO | Assess the veracity of model simulations of the various key NAMS phenomena and the linkages to regional/large-scale climate variability
Examine model simulations at the process level (e.g. convection, land/atmosphere and ocean/atmosphere interactions) |
|  | Influence of stratospheric anomaly on tropospheric climate | QBO, ozone depletion, volcanic eruptions, etc. | Make application as forecast tools |
|  | Impact of solar flux variation A12 |   Role of ocean-atmosphere coupling
  Enhanced by anthropogenic trace gas effect. |  |

**Predictability Studies**

**- A7.2 -**

## R&D Needs Update

|  | Objects |  |     Basic Research             (Hypotheses and Understanding) |  Applied Research            (Applications and Tools) |
| --- | --- | --- | --- | --- |
|  | Atmospheric model  | Cloud | Conception of direct physical interaction of clouds A13 to improve cloud-radiation-Sfc & PBL interaction and precipitation of the model
Supper-parameterizations | Cumulus scheme
Grid-scale microphysiscs
Cloud optical properties
Cloud fraction (with overlap and merging convective grid-scale cloudiness)
Cloud optical depths varying with wave-length (albedo, asymmetry factor, absorption coefficients)
Convection, PBL evolution (growth, decay, stabilization by downdrafts) and precipitation |
|  |  | Radiation | Redistribution of radiative energy due to variations of absorption and scattering media (concentration of trace gases, clouds and aerosols)
Atmospheric radiation and chemistry interaction (ozone production and dissipation by both natural and man-made processes)  | Improve radiation computation conception for non-line (continue) absorption gases
Improve calculation accuracy in the stratosphere
Improve aerosol observation |
|  |  | Stratosphere | Chemistry processes | Vertical hybrid coordinate system  |

**Climate Model and Data Reanalysis**

**- A8.1 -**

## R&D Needs Update

|  | Objects |     Basic Research             (Hypotheses and Understanding) | Applied Research                        (Applications and Tools) |
| --- | --- | --- | --- |
|  | Oceanic model | Improve tropical-subtropical interchanges in western boundary regions and inter-basin exchanges through the Indonesian through-flow. | Improve model sub-grid scale mixing 
Better represent the warm pool in the western Pacific and the cold tongue in the eastern Pacific. |
|  | Ocean data assimilation | Continue development of advanced ocean data assimilation methods and evaluate their possible advantages for operational use | Incorporate Argo float profiles of temperature and salinity and Jason satellite altimetry.
Assess model bias and better estimate model and data error statistics. |
|  | Land surface process simulation and regional climate model | Develop forward radiative transfer model (weigh observation error and model error) | Improve physical parameterization in land model (snow pack, canopy, CO2 flux, etc.)
Remote sensing vegetation properties and solar fluxes |
|  | Sea ice model | Develop sufficiently rigorous performance measures | Implement statistical prediction models.
ssess the duration of skilled prediction from the models.
Determine what is setting limits of skill for models. |
|  | Coupled system and ensemble prediction | Ability to reproduce climatology and variability from intraseasonal to interdecadal time-scales
Understand the impact of coupled feedbacks on model errors A14.1-14.2 |  |
|  | Climate data reanalysis |  | Global and regional climate data reanalysis
Climate data continuity
LDAS Land data reanalysis (1948-1998, 1/8, hourly, 45 variables) |

**Climate Model and Data Reanalysis**

## R&D Needs Update

|  | Objects | Basic Research                   (Hypotheses and Understanding) | Applied Research                (Applications and Tools) |
| --- | --- | --- | --- |
|  | Precipitation data analysis |  | Develop and improve objective techniques capable of providing improved precipitation analyses using additional information from new observations (e.g. new satellites) while maintaining homogeneity in the time series
Develop calibration techniques for satellite observation especially in the steep mountain area with sparse surface observation
Real-time analysis and historic mining of rain gauge data for linking weather and climate |
|  | Variability and maintenance of water cycle | Quantify variability in water cycle
Understand the mechanisms underlying variability in the water cycle 
Distinguish human-induced and natural variations in the water cycle.
Explore the degree of predictability of variations in the water cycle 
Improve predictions of water resources by quantifying fluxes between key hydrologic reservoirs | Establish a systems modeling framework for making predictions and estimates of uncertainty that are useful for water resource management, natural hazard mitigation, decision making, and policy guidance
Integrate Drought/Flood in a Single Product
 |

**Precip data and Hydrologic Science**

**- A9 -**