scholarly journals A 10 km North American precipitation and land-surface reanalysis based on the GEM atmospheric model

2021 ◽  
Vol 25 (9) ◽  
pp. 4917-4945
Author(s):  
Nicolas Gasset ◽  
Vincent Fortin ◽  
Milena Dimitrijevic ◽  
Marco Carrera ◽  
Bernard Bilodeau ◽  
...  
Keyword(s):  
North American ◽  
Land Surface ◽  
Lower Troposphere ◽  
Summer Precipitation ◽  
Atmospheric Model ◽  
Dew Point ◽  
Land Data Assimilation ◽  
Precipitation Analysis ◽  
Land Data Assimilation System ◽  
The Impact

Abstract. Environment and Climate Change Canada has initiated the production of a 1980–2018, 10 km, North American precipitation and surface reanalysis. ERA-Interim is used to initialize the Global Deterministic Reforecast System (GDRS) at a 39 km resolution. Its output is then dynamically downscaled to 10 km by the Regional Deterministic Reforecast System (RDRS). Coupled with the RDRS, the Canadian Land Data Assimilation System (CaLDAS) and Precipitation Analysis (CaPA) are used to produce surface and precipitation analyses. All systems used are close to operational model versions and configurations. In this study, a 7-year sample of the reanalysis (2011–2017) is evaluated. Verification results show that the skill of the RDRS is stable over time and equivalent to that of the current operational system. The impact of the coupling between RDRS and CaLDAS is explored using an early version of the reanalysis system which was run at 15 km resolution for the period 2010–2014, with and without the use of CaLDAS. Significant improvements are observed with CaLDAS in the lower troposphere and surface layer, especially for the 850 hPa dew point and absolute temperatures in summer. Precipitation is further improved through an offline precipitation analysis which allows the assimilation of additional observations of 24 h precipitation totals. The final dataset should be of particular interest for hydrological applications focusing on transboundary and northern watersheds, where existing products often show discontinuities at the border and assimilate very few – if any – precipitation observations.

scholarly journals A 10 km North American Precipitation and Land Surface Reanalysis Based on the GEM Atmospheric Model

2021 ◽  
Author(s):  
Nicolas Gasset ◽  
Vincent Fortin ◽  
Milena Dimitrijevic ◽  
Marco Carrera ◽  
Bernard Bilodeau ◽  
...  
Keyword(s):  
North American ◽  
Land Surface ◽  
Lower Troposphere ◽  
Summer Precipitation ◽  
Atmospheric Model ◽  
Dew Point ◽  
Land Data Assimilation ◽  
Precipitation Analysis ◽  
Land Data Assimilation System ◽  
The Impact

Abstract. Environment and Climate Change Canada has initiated the production of a 1980–2018, 10 km, North American precipitation and surface reanalysis. ERA-Interim is used to initialize the Global Deterministic Reforecast System (GDRS) at a 39 km resolution. Its output is then dynamically downscaled to 10 km by the Regional Deterministic Reforecast System (RDRS). Coupled with the RDRS, the Canadian Land Data Assimilation System (CaLDAS) and Precipitation Analysis (CaPA) are used to produce surface and precipitation analyses. All systems used are close to operational model versions and configurations. In this study, a 7-year sample of the reanalysis (2011–2017) is evaluated. Verification results show that the skill of the RDRS is stable over time, and equivalent to that of the current operational system. The impact of the coupling between RDRS and CaLDAS is explored using an early version of the reanalysis system which was run at 15 km resolution for the period 2010–2014, with and without the use of CaLDAS. Significant improvements are observed with CaLDAS in the lower troposphere and surface layer, especially for the 850 hPa dew point and absolute temperatures in summer. Precipitation is further improved through an offline precipitation analysis which allows the assimilation of additional observations of 24-h precipitation totals. The final dataset should be of particular interest for hydrological applications focusing on trans-boundary and northern watersheds, where existing products often show discontinuities at the border and assimilate very few – if any – precipitation observations.

scholarly journals Similarity Assessment of Land Surface Model Outputs in the North American Land Data Assimilation System

2017 ◽  
Vol 53 (11) ◽  
pp. 8941-8965 ◽  
Author(s):  
Sujay V. Kumar ◽  
Shugong Wang ◽  
David M. Mocko ◽  
Christa D. Peters-Lidard ◽  
Youlong Xia
Keyword(s):  
Data Assimilation ◽  
North American ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
The North ◽  
Land Data Assimilation ◽  
Land Data Assimilation System ◽  
Data Assimilation System ◽  
Assimilation System

scholarly journals From Monitoring to Forecasting Land Surface Conditions Using a Land Data Assimilation System: Application over the Contiguous United States

2020 ◽  
Vol 12 (12) ◽  
pp. 2020 ◽  
Author(s):  
Anthony Mucia ◽  
Bertrand Bonan ◽  
Yongjun Zheng ◽  
Clément Albergel ◽  
Jean-Christophe Calvet
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Data Assimilation ◽  
Land Surface ◽  
Surface Model ◽  
Land Data Assimilation ◽  
Land Data Assimilation System ◽  
The Impact ◽  
Data Assimilation System ◽  
Assimilation System

LDAS-Monde is a global land data assimilation system (LDAS) developed by Centre National de Recherches Météorologiques (CNRM) to monitor land surface variables (LSV) at various scales, from regional to global. With LDAS-Monde, it is possible to jointly assimilate satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the interactions between soil biosphere and atmosphere (ISBA) land surface model (LSM) in order to analyze the soil moisture profile together with vegetation biomass. In this study, we investigate LDAS-Monde’s ability to predict LSV states up to two weeks in the future using atmospheric forecasts. In particular, the impact of the initialization, and the evolution of the forecasted variables in the LSM are addressed. LDAS-Monde is an offline system normally driven by atmospheric reanalysis, but in this study is forced by atmospheric forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) for the 2017–2018 period over the contiguous United States (CONUS) at a 0.2° × 0.2° spatial resolution. These LSV forecasts are initialized either by the model alone (LDAS-Monde open-loop, without assimilation) or by the analysis (assimilation of SSM and LAI). These two forecasts are then evaluated using satellite-derived observations of SSM and LAI, evapotranspiration (ET) estimates, as well as in situ measurements of soil moisture from the U.S. Climate Reference Network (USCRN). Results indicate that for the three evaluation variables (SSM, LAI, and ET), LDAS-Monde provides reasonably accurate and consistent predictions two weeks in advance. Additionally, the initial conditions after assimilation are shown to make a positive impact with respect to LAI and ET. This impact persists in time for these two vegetation-related variables. Many model variables, such as SSM, root zone soil moisture (RZSM), LAI, ET, and drainage, remain relatively consistent as the forecast lead time increases, while runoff is highly variable.

scholarly journals LDAS-Monde Sequential Assimilation of Satellite Derived Observations Applied to the Contiguous US: An ERA-5 Driven Reanalysis of the Land Surface Variables

2018 ◽  
Vol 10 (10) ◽  
pp. 1627 ◽  
Author(s):  
Clement Albergel ◽  
Simon Munier ◽  
Aymeric Bocher ◽  
Bertrand Bonan ◽  
Yongjun Zheng ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Land Surface ◽  
The United States ◽  
Agricultural Drought ◽  
Land Data Assimilation ◽  
Land Data Assimilation System ◽  
The Impact ◽  
Data Assimilation System ◽  
Assimilation System

Land data assimilation system (LDAS)-Monde, an offline land data assimilation system with global capacity, is applied over the CONtiguous US (CONUS) domain to enhance monitoring accuracy for water and energy states and fluxes. LDAS-Monde ingests satellite-derived surface soil moisture (SSM) and leaf area index (LAI) estimates to constrain the interactions between soil, biosphere, and atmosphere (ISBA) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the total runoff integrating pathways (CTRIP) continental hydrological system (ISBA-CTRIP). LDAS-Monde is forced by the ERA-5 atmospheric reanalysis from the European Center for Medium Range Weather Forecast (ECMWF) from 2010 to 2016 leading to a seven-year, quarter degree spatial resolution offline reanalysis of land surface variables (LSVs) over CONUS. The impact of assimilating LAI and SSM into LDAS-Monde is assessed over North America, by comparison to satellite-driven model estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project, and upscaled ground-based observations of gross primary productivity from the FLUXCOM project. Taking advantage of the relatively dense data networks over CONUS, we have also evaluated the impact of the assimilation against in situ measurements of soil moisture from the USCRN (US Climate Reference Network), together with river discharges from the United States Geological Survey (USGS) and the Global Runoff Data Centre (GRDC). Those data sets highlight the added value of assimilating satellite derived observations compared with an open-loop simulation (i.e., no assimilation). It is shown that LDAS-Monde has the ability not only to monitor land surface variables but also to forecast them, by providing improved initial conditions, which impacts persist through time. LDAS-Monde reanalysis also has the potential to be used to monitor extreme events like agricultural drought. Finally, limitations related to LDAS-Monde and current satellite-derived observations are exposed as well as several insights on how to use alternative datasets to analyze soil moisture and vegetation state.

Seasonal-to-Decadal Predictability and Prediction of North American Climate—The Atlantic Influence

2006 ◽  
Vol 19 (23) ◽  
pp. 6005-6024 ◽  
Author(s):  
H. M. Van den Dool ◽  
Peitao Peng ◽  
Åke Johansson ◽  
Muthuvel Chelliah ◽  
Amir Shabbar ◽  
...  
Keyword(s):  
North American ◽  
Seasonal Prediction ◽  
Atmospheric Model ◽  
The United States ◽  
Seasonal Forecast ◽  
Ocean Model ◽  
Prediction Skill ◽  
Basic Material ◽  
Atlantic Sector ◽  
The Impact

Abstract The question of the impact of the Atlantic on North American (NA) seasonal prediction skill and predictability is examined. Basic material is collected from the literature, a review of seasonal forecast procedures in Canada and the United States, and some fresh calculations using the NCEP–NCAR reanalysis data. The general impression is one of low predictability (due to the Atlantic) for seasonal mean surface temperature and precipitation over NA. Predictability may be slightly better in the Caribbean and the (sub)tropical Americas, even for precipitation. The NAO is widely seen as an agent making the Atlantic influence felt in NA. While the NAO is well established in most months, its prediction skill is limited. Year-round evidence for an equatorially displaced version of the NAO (named ED_NAO) carrying a good fraction of the variance is also found. In general the predictability from the Pacific is thought to dominate over that from the Atlantic sector, which explains the minimal number of reported Atmospheric Model Intercomparison Project (AMIP) runs that explore Atlantic-only impacts. Caveats are noted as to the question of the influence of a single predictor in a nonlinear environment with many predictors. Skill of a new one-tier global coupled atmosphere–ocean model system at NCEP is reviewed; limited skill is found in midlatitudes and there is modest predictability to look forward to. There are several signs of enthusiasm in the community about using “trends” (low-frequency variations): (a) seasonal forecast tools include persistence of last 10 years’ averaged anomaly (relative to the official 30-yr climatology), (b) hurricane forecasts are based largely on recognizing a global multidecadal mode (which is similar to an Atlantic trend mode in SST), and (c) two recent papers, one empirical and one modeling, giving equal roles to the (North) Pacific and Atlantic in “explaining” variations in drought frequency over NA on a 20 yr or longer time scale during the twentieth century.

scholarly journals Land–atmosphere interactions in the tropics

2019 ◽  
Author(s):  
Pierre Gentine ◽  
Adam Massmann ◽  
Benjamin R. Lintner ◽  
Sayed Hamed Alemohammad ◽  
Rong Fu ◽  
...  
Keyword(s):  
Land Surface ◽  
Deep Convection ◽  
Lower Troposphere ◽  
Surface Fluxes ◽  
Surface Radiation ◽  
Spatial And Temporal Scales ◽  
Wide Range ◽  
Shallow Clouds ◽  
The Tropics ◽  
The Impact

Abstract. The continental tropics play a leading role in the terrestrial water and carbon cycles. Land–atmosphere interactions are integral in the regulation of surface energy, water and carbon fluxes across multiple spatial and temporal scales over tropical continents. We review here some of the important characteristics of tropical continental climates and how land–atmosphere interactions regulate them. Along with a wide range of climates, the tropics manifest a diverse array of land–atmosphere interactions. Broadly speaking, in tropical rainforests, light and energy are typically more limiting than precipitation and water supply for photosynthesis and evapotranspiration; whereas in savanna and semi-arid regions water is the critical regulator of surface fluxes and land–atmosphere interactions. We discuss the impact of the land surface, how it affects shallow clouds and how these clouds can feedback to the surface by modulating surface radiation. Some results from recent research suggest that shallow clouds may be especially critical to land–atmosphere interactions as these regulate the energy budget and moisture transport to the lower troposphere, which in turn affects deep convection. On the other hand, the impact of land surface conditions on deep convection appear to occur over larger, non-local, scales and might be critically affected by transitional regions between the climatologically dry and wet tropics.

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