scholarly journals Improving Regional Model Simulations with Precipitation Assimilation

2005 ◽  
Vol 9 (20) ◽  
pp. 1-44 ◽  
Author(s):  
Ana M. B. Nunes ◽  
John O. Roads
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Initial Conditions ◽  
Regional Model ◽  
Seasonal Forecasts ◽  
Wet Season ◽  
Model Simulations ◽  
Precipitation Simulation ◽  
Global Reanalysis ◽  
Model Precipitation

Abstract Although large-scale atmospheric reanalyses are now providing physical, realistic fields for many variables, precipitation remains problematic. As shown in recent studies, using a regional model to downscale the global reanalysis only marginally alleviates the precipitation simulation problems. For this reason, later-generation analyses, including the recent National Centers for Environmental Prediction regional reanalysis, are using precipitation assimilation as a methodology to provide superior precipitation fields. This methodology can also be applied to regional model simulations to substantially improve the precipitation fields downscaled from global reanalysis. As an illustration of the regional model precipitation assimilation impact, the authors describe here an extended-range simulation comparison over South America. The numerical experiments cover the beginning of the Large-Scale Biosphere–Atmosphere wet season campaign of January 1999. Evaluations using radiosonde datasets obtained during this campaign are provided as well. As will be shown, rain-rate assimilation not only increases the regional model precipitation simulation skill but also provides improvements in other fields influenced by the precipitation. Because of the potential impact on land surface features, the authors believe they will ultimately be able to show improvements in monthly to seasonal forecasts when precipitation assimilation is used to generate more accurate land surface initial conditions.

scholarly journals The DeepMIP contribution to PMIP4: experimental design for model simulations of the EECO, PETM, and pre-PETM (version 1.0)

2017 ◽  
Vol 10 (2) ◽  
pp. 889-901 ◽  
Author(s):  
Daniel J. Lunt ◽  
Matthew Huber ◽  
Eleni Anagnostou ◽  
Michiel L. J. Baatsen ◽  
Rodrigo Caballero ◽  
...  
Keyword(s):  
Experimental Design ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Initial Conditions ◽  
Geological Data ◽  
Time Model ◽  
Model Simulations ◽  
Intercomparison Project ◽  
Climate Model Simulations

Abstract. Past warm periods provide an opportunity to evaluate climate models under extreme forcing scenarios, in particular high ( >  800 ppmv) atmospheric CO2 concentrations. Although a post hoc intercomparison of Eocene ( ∼  50  Ma) climate model simulations and geological data has been carried out previously, models of past high-CO2 periods have never been evaluated in a consistent framework. Here, we present an experimental design for climate model simulations of three warm periods within the early Eocene and the latest Paleocene (the EECO, PETM, and pre-PETM). Together with the CMIP6 pre-industrial control and abrupt 4 ×  CO2 simulations, and additional sensitivity studies, these form the first phase of DeepMIP – the Deep-time Model Intercomparison Project, itself a group within the wider Paleoclimate Modelling Intercomparison Project (PMIP). The experimental design specifies and provides guidance on boundary conditions associated with palaeogeography, greenhouse gases, astronomical configuration, solar constant, land surface processes, and aerosols. Initial conditions, simulation length, and output variables are also specified. Finally, we explain how the geological data sets, which will be used to evaluate the simulations, will be developed.

General Characteristics and Variability of Climate in the Amazon Basin and its Links to the Global Climate System

2001 ◽  
Author(s):  
Jose A. Marengo ◽  
Carlos A. Nobre
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Amazon Basin ◽  
Global Climate ◽  
River System ◽  
Climate System ◽  
Wet Season ◽  
Tropospheric Circulation ◽  
The Tropics

The Amazon region is of particular interest because it represents a large source of heat in the tropics and has been shown to have a significant impact on extratropical circulation, and it is Earth’s largest and most intense land-based convective center. During the Southern Hemisphere summer when convection is best developed, the Amazon basin is one of the wettest regions on Earth. Amazonia is of course not isolated from the rest of the world, and a global perspective is needed to understand the nature and causes of climatological anomalies in Amazonia and how they feed back to influence the global climate system. The Amazon River system is the single, largest source of freshwater on Earth. The flow regime of this river system is relatively unimpacted by humans (Vörösmarty et al. 1997 a, b) and is subject to interannual variability in tropical precipitation that ultimately is translated into large variations in downstream hydrographs (Marengo et al. 1998a, Vörösmarty et al. 1996, Richey et al. 1989a, b). The recycling of local evaporation and precipitation by the forest accounts for a sizable portion of the regional water budget (Nobre et al. 1991, Eltahir 1996), and as large areas of the basin are subject to active deforestation there is grave concern about how such land surface disruptions may affect the water cycle in the tropics (see reviews in Lean et al. 1996). Previous studies have emphasized either how large-scale atmospheric circulation or land surface conditions can directly control the seasonal changes in rainfall producing mechanisms. Studies invoking controls of convection and rainfall by large-scale circulation emphasize the relationship between the establishment of upper-tropospheric circulation over Bolivia and moisture transport from the Atlantic ocean for initiation of the wet season and its intensity (see reviews in Marengo et al. 1999). On the other hand, Eltahir and Pal (1996) have shown that Amazon convection is closely related to land surface humidity and temperature, while Fu et al. (1999) indicate that the wet season in the Amazon basin is controlled by both changes in land surface temperature and the sea surface temperature (SST) in the adjacent oceans, depending if the region is north-equatorial or southern Amazonia.

scholarly journals Precipitation and cloud cellular structures in marine stratocumulus over the southeast pacific: model simulations

2010 ◽  
Vol 10 (3) ◽  
pp. 8341-8378
Author(s):  
H. Wang ◽  
G. Feingold ◽  
R. Wood ◽  
J. Kazil
Keyword(s):  
Boundary Layer ◽  
Large Scale ◽  
Initial Conditions ◽  
Sensible Heat Flux ◽  
Cell Formation ◽  
Solar Heating ◽  
Cellular Structures ◽  
Open Cell ◽  
Model Simulations ◽  
Southeast Pacific

Abstract. Microphysical and meteorological controls on the formation of open and closed cellular structures in the Southeast Pacific are explored using model simulations based on aircraft observations during the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx). The effectiveness of factors such as boundary-layer moisture and temperature perturbations, surface heat and moisture fluxes, large-scale vertical motion and solar heating in promoting drizzle and open cell formation for prescribed aerosol number concentrations is explored. For the case considered, drizzle and subsequent open cell formation over a broad region are more sensitive to the observed boundary-layer moisture and temperature perturbations (=0.9 g kg−1; −1 K) than to a five-fold decrease in aerosol number concentrations (150 vs. 30 mg−1). When embedding the perturbations in closed cells, local drizzle and pockets of open cells (POCs) formation respond faster to the aerosol reduction than to the moisture increase, but the latter generate stronger and more persistent drizzle. The local negative perturbation in temperature drives a mesoscale circulation that prevents local drizzle formation but promotes it in a remote area where lower-level horizontal transport of moisture is blocked and converges to enhance liquid water path. This represents a potential mechanism for POC formation in the Southeast Pacific stratocumulus region whereby the circulation is triggered by strong precipitation in adjacent broad regions of open cells. A simulation that attempts to mimic the influence of a coastally induced upsidence wave results in an increase in cloud water but this alone is insufficient to initiate drizzle. An increase of surface sensible heat flux is also effective in triggering local drizzle and POC formation. Both open and closed cells simulated with observed initial conditions exhibit distinct diurnal variations in cloud properties. A stratocumulus deck that breaks up due solely to solar heating can recover at night. Precipitation in the open-cell cases depletes the aerosol to the extent that cloud formation is significantly suppressed within one diurnal cycle. A replenishment rate of cloud condensation nuclei of 0.72 mg−1 h−1 is sufficient to maintain clouds and prevent the boundary layer from collapsing the following day, suggesting that some local and/or remote aerosol sources are necessary for POCs to be able to last for days.

scholarly journals A Combined Approach to Improving the Regional Model Forecasts for the Rainy Season in China

2017 ◽  
Vol 145 (11) ◽  
pp. 4593-4603
Author(s):  
Yanfeng Zhao ◽  
Donghai Wang ◽  
Jianjun Xu
Keyword(s):  
Rainy Season ◽  
Large Scale ◽  
Initial Conditions ◽  
Wrf Model ◽  
Regional Model ◽  
Weather Research And Forecasting ◽  
Small Scale ◽  
Wind Fields ◽  
Accumulated Rainfall ◽  
Combined Forecasting

A combined forecasting methodology, into which the spectral nudging, lateral boundary filtering, and update initial conditions methods are incorporated, was employed in the regional Weather Research and Forecasting (WRF) Model. The intent was to investigate the potential for improving the prediction capability for the rainy season in China via using as many merits of the global model having better predictability as it does for the large-scale circulation and of the regional model as it does for the small-scale features. The combined methodology was found to be successful in improving the prediction of the regional atmospheric circulation and precipitation. It performed best for the larger magnitude precipitation, the relative humidity above 800 hPa, and wind fields below 300 hPa. Furthermore, the larger the magnitude and the longer the lead time, the more obvious is the improvement in terms of the accumulated rainfall of persistent severe rainfall events.

scholarly journals Impact of Atmosphere and Land Surface Initial Conditions on Seasonal Forecasts of Global Surface Temperature

2014 ◽  
Vol 27 (24) ◽  
pp. 9253-9271 ◽  
Author(s):  
Stefano Materia ◽  
Andrea Borrelli ◽  
Alessio Bellucci ◽  
Andrea Alessandri ◽  
Pierluigi Di Pietro ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Initial Conditions ◽  
Seasonal Prediction ◽  
Forecast Skill ◽  
Seasonal Forecasts ◽  
Initial State ◽  
Predictive Skill ◽  
The Impact ◽  
Initialization Strategy

Abstract The impact of land surface and atmosphere initialization on the forecast skill of a seasonal prediction system is investigated, and an effort to disentangle the role played by the individual components to the global predictability is done, via a hierarchy of seasonal forecast experiments performed under different initialization strategies. A realistic atmospheric initial state allows an improved equilibrium between the ocean and overlying atmosphere, increasing the model predictive skill in the ocean. In fact, in regions characterized by strong air–sea coupling, the atmosphere initial condition affects forecast skill for several months. In particular, the ENSO region, eastern tropical Atlantic, and North Pacific benefit significantly from the atmosphere initialization. On the mainland, the effect of atmospheric initial conditions is detected in the early phase of the forecast, while the quality of land surface initialization affects forecast skill in the following seasons. Winter forecasts in the high-latitude plains benefit from the snow initialization, while the impact of soil moisture initial state is particularly effective in the Mediterranean region and central Asia. However, the initialization strategy based on the full value technique may not be the best choice for land surface, since soil moisture is a strongly model-dependent variable: in fact, initialization through land surface reanalysis does not systematically guarantee a skill improvement. Nonetheless, using a different initialization strategy for land, as opposed to atmosphere and ocean, may generate inconsistencies. Overall, the introduction of a realistic initialization for land and atmosphere substantially increases skill and accuracy. However, further developments in the procedure for land surface initialization are required for more accurate seasonal forecasts.

scholarly journals Satellite-based modelling of potential tsetse (Glossina pallidipes) breeding and foraging sites using teneral and non-teneral fly occurrence data

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Stella Gachoki ◽  
Thomas Groen ◽  
Anton Vrieling ◽  
Michael Okal ◽  
Andrew Skidmore ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Land Surface ◽  
Large Scale ◽  
Model Performance ◽  
Glossina Pallidipes ◽  
Tsetse Flies ◽  
Wet Season ◽  
Distribution Models ◽  
Breeding Sites ◽  
Occurrence Data

Abstract Background African trypanosomiasis, which is mainly transmitted by tsetse flies (Glossina spp.), is a threat to public health and a significant hindrance to animal production. Tools that can reduce tsetse densities and interrupt disease transmission exist, but their large-scale deployment is limited by high implementation costs. This is in part limited by the absence of knowledge of breeding sites and dispersal data, and tools that can predict these in the absence of ground-truthing. Methods In Kenya, tsetse collections were carried out in 261 randomized points within Shimba Hills National Reserve (SHNR) and villages up to 5 km from the reserve boundary between 2017 and 2019. Considering their limited dispersal rate, we used in situ observations of newly emerged flies that had not had a blood meal (teneral) as a proxy for active breeding locations. We fitted commonly used species distribution models linking teneral and non-teneral tsetse presence with satellite-derived vegetation cover type fractions, greenness, temperature, and soil texture and moisture indices separately for the wet and dry season. Model performance was assessed with area under curve (AUC) statistics, while the maximum sum of sensitivity and specificity was used to classify suitable breeding or foraging sites. Results Glossina pallidipes flies were caught in 47% of the 261 traps, with teneral flies accounting for 37% of these traps. Fitted models were more accurate for the teneral flies (AUC = 0.83) as compared to the non-teneral (AUC = 0.73). The probability of teneral fly occurrence increased with woodland fractions but decreased with cropland fractions. During the wet season, the likelihood of teneral flies occurring decreased as silt content increased. Adult tsetse flies were less likely to be trapped in areas with average land surface temperatures below 24 °C. The models predicted that 63% of the potential tsetse breeding area was within the SHNR, but also indicated potential breeding pockets outside the reserve. Conclusion Modelling tsetse occurrence data disaggregated by life stages with time series of satellite-derived variables enabled the spatial characterization of potential breeding and foraging sites for G. pallidipes. Our models provide insight into tsetse bionomics and aid in characterising tsetse infestations and thus prioritizing control areas. Graphical abstract

scholarly journals Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): Organization and Experimental design

2021 ◽  
Author(s):  
Yongkang Xue ◽  
Tandong Yao ◽  
Aaron A. Boone ◽  
Ismaila Diallo ◽  
Ye Liu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Initial Conditions ◽  
Yangtze River Basin ◽  
Seasonal Prediction ◽  
High Mountain ◽  
The Tibetan Plateau

Abstract. Sub-seasonal to seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging but has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges (GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative called Impact of initialized Land Surface temperature and Snowpack on Sub-seasonal to Seasonal Prediction (LS4P), as the first international grass-root effort to introduce spring land surface temperature (LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a crucial factor that can lead to significant improvement in precipitation prediction through the remote effects of land/atmosphere interactions. LS4P focuses on process understanding and predictability, hence it is different from, and complements, other international projects that focus on the operational S2S prediction. More than forty groups worldwide have participated in this effort, including 21 Earth System Models, 9 regional climate models, and 7 data groups. This paper overviews the history and objectives of LS4P, provides the first phase experimental protocol (LS4P-I) which focuses on the remote effect of the Tibetan Plateau, discusses the LST/SUBT initialization, and presents the preliminary results. Multi-model ensemble experiments and analyses of observational data have revealed that the hydroclimatic effect of the spring LST in the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation and its S2S prediction. LS4P models are unable to preserve the initialized LST anomalies in producing the observed anomalies largely for two main reasons: i) inadequacies in the land models arising from total soil depths which are too shallow and the use of simplified parameterizations which both tend to limit the soil memory; and ii) reanalysis data, that are used for initial conditions, have large discrepancies from the observed mean state and anomalies of LST over the Tibetan Plateau. Innovative approaches have been developed to largely overcome these problems.

ULYSSES: a system for global multi-model hydrological seasonal predictions

2021 ◽  
Author(s):  
Luis Samaniego ◽  
Stephan Thober ◽  
Matthias Kelbling ◽  
Robert Schweppe ◽  
Oldrich Rakovec ◽  
...  
Keyword(s):  
Land Surface ◽  
Snow Water Equivalent ◽  
Initial Conditions ◽  
Model Performance ◽  
Seasonal Prediction ◽  
Climate Data ◽  
Seasonal Forecasts ◽  
Climate Services ◽  
Production Chain ◽  
Data Store

<p>The Copernicus Climate Change Service aims at facilitating the emergence of a downstream market of climate services with the ultimate goal of supporting the development of a climate-smart society. Central to this vision is the free and unrestricted distribution of high-quality climate data through the Climate Data Store [1], with seasonal meteorological predictions among them. Within this unique and challenging framework, ULYSSES [2] will provide the first "seamless'' multi-model hydrological seasonal prediction system, with a global coverage at a spatial resolution of 0.1° The ULYSSES modeling chain is based on the successfully tested EDgE proof of concept [3] using four state-of-the-art hydrological models (Jules, HTESSEL, mHM, and PCR-GLOBWB). A unique feature of this production chain consists of using the same land surface datasets (e.g. DEM, soil properties) with identical spatio-temporal resolutions and forecast inputs for all HMs, and the same river routing scheme (i.e., the multi-scale routing model mRM).</p><p>The initial conditions of the production chain will be based on ERA5-Land dataset and the seasonal forecasts will be driven by a 25-member ensemble generated by the ECMWF-SEAS5 model. ULYSSES aims at generating six essential hydrological variables: snow-water equivalent, snowmelt, evapotranspiration, soil moisture, total runoff, and streamflow with a lead-time of up to six months.  The seasonal forecast was verified at 250+ gauges distributred in all continents during the hind-casting period from 1993 to 2019. The operational forecasting period —in testing phase— started in January 2021 and be extended through until July 2021.  The first operational ULYSSES forecast will be made available by the 10th of each month starting in January 2021.</p><p>All input data sets (ERA5-Land), seasonal forecasts (SEAS5) and ULYSSES outputs will be made available in the Copernicus Climate Data Store [1] and will be open access. We aim to engage institutions and researchers around the world that are willing to evaluate the forecasts model performance, with the aim of improving the system in the future. In this talk, the modelling chain concept, model setup and verification of initial results will be presented.</p><ul><li>[1] https://cds.climate.copernicus.eu</li> <li>[2] https://www.ufz.de/ulysses</li> <li>[3] https://doi.org/10.1175/BAMS-D-17-0274.1</li> </ul>

scholarly journals A model for simulating the deposition of water-lain sediments in dryland environments

2004 ◽  
Vol 8 (2) ◽  
pp. 122-134 ◽  
Author(s):  
M. A. Bunch ◽  
R. Mackay ◽  
J. H. Tellam ◽  
P. Turner
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Initial Conditions ◽  
Sedimentary Facies ◽  
Storm Event ◽  
Storm Events ◽  
Near Surface ◽  
Radial Profiles ◽  
Long Time ◽  
The Uk

Abstract. A numerical process-imitating model, the Discrete Storm Event Sedimentation Simulator (DSESS), has been developed to represent the climatic and hydraulic conditions of drylands in modelling their geomorphological development and sedimentary facies distributions. The ultimate aim is to provide insights into the lateral variability of permeability in the Triassic Sandstone aquifers of the UK for the study of solute movement. DSESS employs discrete storm-flood automata, released across a cellular landscape, to model sediment transport: erosion, migration and deposition. Sediment classes with different grain sizes can be modelled. Empirical process-based equations are used to quantify the movement of the automata, their erosion potential, sediment-carrying capacity and interaction with the underlying sediments. The approach emphasises the sequence of dryland storm events and associated floods rather than their timing. Flood events are assumed to be discrete in time. Preliminary tests carried out with DSESS using simple systems and idealised initial conditions produce lithological and land surface features characteristic of dryland settings and indicate the potential of the model for large-scale, long-time modelling of sedimentary facies development. Markedly different results are observed across the range of tests carried out in response to the non-linear interactions between the different elements of the landscape and the floodwaters simulated with DSESS. Simulations show that sediment accumulations develop concave upward radial profiles, plano-convex cross-profiles and possess a general lateral grading of sediment with distance from source. The internal grain size architecture shows evidence of both persistent and rapidly changing flow conditions, with both lateral and longitudinal stepping of coarse bodies produced by ‘scour and fill’ events and random avulsions. Armoured layers form so that near-surface sediments have increased likelihood of preservation. Future developments will include representation of aeolian deposition, mass wasting and hyper-concentrated (debris) flows. Keywords: avulsion, channel, deposition, drylands, erosion, gravel armouring, modelling, sheet-flood, transport capacity

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