scholarly journals Estimation of the Terrestrial Water Budget over Northern Eurasia through the Use of Multiple Data Sources

2011 ◽  
Vol 24 (13) ◽  
pp. 3272-3293 ◽  
Author(s):  
Tara J. Troy ◽  
Justin Sheffield ◽  
Eric F. Wood
Keyword(s):  
Water Budget ◽  
Large Scale ◽  
Cold Season ◽  
Northern Eurasia ◽  
Past Century ◽  
Multiple Sources ◽  
Multiple Data ◽  
Terrestrial Water ◽  
The Mean

Abstract Northern Eurasia has experienced significant change in its hydrology during the past century. Much of the literature has focused on documenting and understanding the trends rather than documenting the uncertainty that exists in current estimates of the mean hydroclimatology. This study quantifies the terrestrial water budget with reanalysis, hydrologic modeling, remote sensing, and in situ observations and shows there is significant uncertainty in the estimates of precipitation, evapotranspiration, runoff, and terrestrial water storage changes. The spread among the various datasets highlights the scientific community's inability to accurately characterize the hydroclimatology of this region, which is problematic because much attention has focused on hydrologic trends using these datasets. The largest relative differences among estimates exist in the terrestrial storage change, which also is the least studied variable. Seasonally, the spread in estimates relative to the mean is largest in winter, when uncertainty in cold-season processes and measurements causes large differences in the estimates. A methodology is developed that takes advantage of multiple sources of data and observed discharge to improve estimates of precipitation, evapotranspiration, and storage changes. The method also provides a framework to evaluate the errors in datasets for variables that have no large-scale in situ measurements, such as evapotranspiration.

Sea surface salinity reemergence in an updated North Atlantic in-situ salinity data set

2021 ◽  
pp. 1-49
Author(s):  
Claude Frankignoul ◽  
Elodie Kestenare ◽  
Gilles Reverdin
Keyword(s):  
Large Scale ◽  
Cold Season ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Data Set ◽  
Salinity Data ◽  
Deep Mixed Layer ◽  
Geostrophic Advection

AbstractMonthly sea surface salinity (SSS) fields are constructed from observations, using objective mapping on a 1°x1° grid in the Atlantic between 30°S and 50°N in the 1970-2016 period in an update of the data set of Reverdin et al. (2007). Data coverage is heterogeneous, with increased density in 2002 when Argo floats become available, high density along Voluntary Observing Ship lines, and low density south of 10°S. Using lag correlation, the seasonal reemergence of SSS anomalies is investigated between 20°N and 50°N in 5°x5° boxes during the 1993-2016 period, both locally and remotely following the displacements of the deep mixed-layer waters estimated from virtual float trajectories derived from the daily AVISO surface geostrophic currents. Although SSS data are noisy, local SSS reemergence is detected in about half of the boxes, notably in the northeast and southeast, while little reemergence is seen in the central and part of the eastern subtropical gyre. In the same period, sea surface temperature (SST) reemergence is found only slightly more frequently, reflecting the short data duration. However, taking geostrophic advection into account degrades the detection of remote SSS and even SST reemergence. When anomalies are averaged over broader areas, robust evidence of a second and third SSS reemergence peak is found in the northeastern and southeastern parts of the domain, indicating long cold-season persistence of large-scale SSS anomalies, while only a first SST reemergence is seen. An oceanic reanalysis is used to confirm that the correlation analysis indeed reflects the reemergence of subsurface salinity anomalies.

scholarly journals What Is the Impact of Additional Tropical Observations on a Modern Data Assimilation System?

2019 ◽  
Vol 147 (7) ◽  
pp. 2433-2449
Author(s):  
Laura C. Slivinski ◽  
Gilbert P. Compo ◽  
Jeffrey S. Whitaker ◽  
Prashant D. Sardeshmukh ◽  
Jih-Wang A. Wang ◽  
...  
Keyword(s):  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Mean Square ◽  
Observational Network ◽  
In Situ Observations ◽  
The Mean ◽  
The Impact ◽  
Assimilation System

Abstract Given the network of satellite and aircraft observations around the globe, do additional in situ observations impact analyses within a global forecast system? Despite the dense observational network at many levels in the tropical troposphere, assimilating additional sounding observations taken in the eastern tropical Pacific Ocean during the 2016 El Niño Rapid Response (ENRR) locally improves wind, temperature, and humidity 6-h forecasts using a modern assimilation system. Fields from a 50-km reanalysis that assimilates all available observations, including those taken during the ENRR, are compared with those from an otherwise-identical reanalysis that denies all ENRR observations. These observations reveal a bias in the 200-hPa divergence of the assimilating model during a strong El Niño. While the existing observational network partially corrects this bias, the ENRR observations provide a stronger mean correction in the analysis. Significant improvements in the mean-square fit of the first-guess fields to the assimilated ENRR observations demonstrate that they are valuable within the existing network. The effects of the ENRR observations are pronounced in levels of the troposphere that are sparsely observed, particularly 500–800 hPa. Assimilating ENRR observations has mixed effects on the mean-square difference with nearby non-ENRR observations. Using a similar system but with a higher-resolution forecast model yields comparable results to the lower-resolution system. These findings imply a limited improvement in large-scale forecast variability from additional in situ observations, but significant improvements in local 6-h forecasts.

scholarly journals Past terrestrial water storage (1980–2008) in the Amazon Basin reconstructed from GRACE and in situ river gauging data

2011 ◽  
Vol 15 (2) ◽  
pp. 533-546 ◽  
Author(s):  
M. Becker ◽  
B. Meyssignac ◽  
L. Xavier ◽  
A. Cazenave ◽  
R. Alkama ◽  
...  
Keyword(s):  
Large Scale ◽  
Amazon Basin ◽  
Hydrological Modeling ◽  
Water Cycle ◽  
Southern Oscillation ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Direct Estimate ◽  
Terrestrial Water

Abstract. Terrestrial water storage (TWS) composed of surface waters, soil moisture, groundwater and snow where appropriate, is a key element of global and continental water cycle. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) space gravimetry mission provides a new tool to measure large-scale TWS variations. However, for the past few decades, direct estimate of TWS variability is accessible from hydrological modeling only. Here we propose a novel approach that combines GRACE-based TWS spatial patterns with multi-decadal-long in situ river level records, to reconstruct past 2-D TWS over a river basin. Results are presented for the Amazon Basin for the period 1980–2008, focusing on the interannual time scale. Results are compared with past TWS estimated by the global hydrological model ISBA-TRIP. Correlations between reconstructed past interannual TWS variability and known climate forcing modes over the region (e.g., El Niño-Southern Oscillation and Pacific Decadal Oscillation) are also estimated. This method offers new perspective for improving our knowledge of past interannual TWS in world river basins where natural climate variability (as opposed to direct anthropogenic forcing) drives TWS variations.

scholarly journals A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010

2018 ◽  
Vol 22 (1) ◽  
pp. 241-263 ◽  
Author(s):  
Yu Zhang ◽  
Ming Pan ◽  
Justin Sheffield ◽  
Amanda L. Siemann ◽  
Colby K. Fisher ◽  
...  
Keyword(s):  
Water Budget ◽  
Water Cycle ◽  
Data Sources ◽  
Climate Data ◽  
Data Set ◽  
Data Record ◽  
Terrestrial Water ◽  
In Situ Observations ◽  
Climate Data Record

Abstract. Closing the terrestrial water budget is necessary to provide consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g., in situ observation, satellite remote sensing, land surface model, and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. Conditioned on the current limited data availability, a systematic method is developed to optimally combine multiple available data sources for precipitation (P), evapotranspiration (ET), runoff (R), and the total water storage change (TWSC) at 0.5∘ spatial resolution globally and to obtain water budget closure (i.e., to enforce P-ET-R-TWSC= 0) through a constrained Kalman filter (CKF) data assimilation technique under the assumption that the deviation from the ensemble mean of all data sources for the same budget variable is used as a proxy of the uncertainty in individual water budget variables. The resulting long-term (1984–2010), monthly 0.5∘ resolution global terrestrial water cycle Climate Data Record (CDR) data set is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This data set serves to bridge the gap between sparsely gauged regions and the regions with sufficient in situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS), and ET from FLUXNET. The data set is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.

scholarly journals A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010

2017 ◽  
Author(s):  
Yu Zhang ◽  
Ming Pan ◽  
Justin Sheffield ◽  
Amanda Siemann ◽  
Colby Fisher ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Water Budget ◽  
Water Cycle ◽  
Data Sources ◽  
Climate Data ◽  
Data Record ◽  
Terrestrial Water ◽  
In Situ Observations ◽  
Climate Data Record

Abstract. Closing the terrestrial water budget is necessary to providing consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in-situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g. in-situ observation, satellite remote sensing, land surface model and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. In this study, a systematic method is developed to optimally combine multiple available data sources for precipitation (P), evapotranspiration (ET), runoff (R) and the total water storage change (TWSC) at 0.5° spatial resolution globally and to obtain water budget closure (i.e. to enforce P − ET − R − TWSC = 0) through a Constrained Kalman Filter (CKF) data assimilation technique. The resulting long-term (1984–2010), monthly, 0.5° resolution global terrestrial water cycle Climate Data Record (CDR) dataset is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This dataset serves to bridge the gap between sparsely gauged regions and the regions with sufficient in-situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in-situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS) and ET from FLUXNET. The dataset is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.

 Generation of planetary waves by gravity-wave drag in the middle atmosphere

2021 ◽  
Author(s):  
Hye-Yeong Chun ◽  
Byeong-Gwon Song ◽  
In-Sun Song
Keyword(s):  
Large Scale ◽  
Middle Atmosphere ◽  
Weather Forecasting ◽  
Wave Theory ◽  
Wave Drag ◽  
Planetary Waves ◽  
Mean Flow ◽  
Long Time ◽  
The Mean

<p>Large-scale atmospheric circulation has been represented mostly by interaction between the mean flow and planetary waves (PWs). Although the importance of gravity waves (GWs) has been recognized for long time, contribution of GWs to the large-scale circulation is receiving more attention recently, with conjunction to GW drag (GWD) parameterizations for climate and global weather forecasting models that extend to the middle atmosphere. As magnitude of GWD increases with height significantly, circulations in the middle atmosphere are determined largely by interactions among the mean flow, PWs and GWs. Classical wave theory in the middle atmosphere has been represented mostly by the Transformed Eulerian Mean (TEM) equation, which include PW and GW forcing separately to the mean flow. Recently, increasing number of studies revealed that forcing by combined PWs and GWs is the same, regardless of different PW and GW forcings, implying a compensation between PWs and GWs forcing. There are two ways for GWs to influence on PWs: (i) changing the mean flow that either influences on waveguide of PWs or induces baroclinic/brotropic instabilities to generate in situ PWs, and (ii) generating PWs as a source of potential vorticity (PV) equation when asymmetric components of GWD exist. The fist mechanism has been studies extensively recently associated with stratospheric sudden warmings (SSWs) that are involved large amplitude PWs and GWD. The second mechanism represents more directly the relationship between PWs and GWs, which is essential to understand the dynamics in the middle atmosphere completely (among the mean flow, PWs and GWs). In this talk, a recently reported result of the generation of PWs by GWs associated with the strongest vortex split-type SSW event occurred in January 2009 (Song et al. 2020, JAS) is presented focusing on the second mechanism.  </p>

scholarly journals Multisource Estimation of Long-Term Terrestrial Water Budget for Major Global River Basins

2012 ◽  
Vol 25 (9) ◽  
pp. 3191-3206 ◽  
Author(s):  
Ming Pan ◽  
Alok K. Sahoo ◽  
Tara J. Troy ◽  
Raghuveer K. Vinukollu ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
Water Balance ◽  
Error Analysis ◽  
Land Surface ◽  
Water Budget ◽  
Large Scale ◽  
Land Surface Model ◽  
Data Sources ◽  
Surface Model ◽  
Terrestrial Water

A systematic method is proposed to optimally combine estimates of the terrestrial water budget from different data sources and to enforce the water balance constraint using data assimilation techniques. The method is applied to create global long-term records of the terrestrial water budget by merging a number of global datasets including in situ observations, remote sensing retrievals, land surface model simulations, and global reanalyses. The estimation process has three steps. First, a conventional analysis on the errors and biases in different data sources is conducted based on existing validation/error studies and other information such as sensor network density, model physics, and calibration procedures. Then, the data merging process combines different estimates so that biases and errors from different data sources can be compensated to the greatest extent and the merged estimates have the best possible confidence. Finally, water balance errors are resolved using the constrained Kalman filter technique. The procedure is applied to 32 globally distributed major basins for 1984–2006. The authors believe that the resulting global water budget estimates can be used as a baseline dataset for large-scale diagnostic studies, for example, integrated assessment of basin water resources, trend analysis and attribution, and climate change studies. The global scale of the analysis presents significant challenges in carrying out the error analysis for each water budget variable. For some variables (e.g., evapotranspiration) the assumptions underpinning the error analysis lack supporting quantitative analysis and, thus, may not hold for specific locations. Nevertheless, the merging and water balance constraining technique can be applied to many problems.

scholarly journals Past terrestrial water storage (1980–2008) in the Amazon Basin reconstructed from GRACE and in situ river gauging data

2010 ◽  
Vol 7 (5) ◽  
pp. 8125-8155
Author(s):  
M. Becker ◽  
B. Meyssignac ◽  
L. Xavier ◽  
R. Alkama ◽  
B. Decharme
Keyword(s):  
Large Scale ◽  
Amazon Basin ◽  
Hydrological Modeling ◽  
Water Cycle ◽  
Southern Oscillation ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Direct Estimate ◽  
Terrestrial Water

Abstract. Terrestrial water storage (TWS) composed of surface waters, soil moisture, groundwater and snow where appropriate, is a key element of global and continental water cycle. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) space gravimetry mission provides a new tool to measure large-scale TWS variations. However, for the past few decades, direct estimate of TWS variability is accessible from hydrological modeling only. Here we propose a novel approach that combines GRACE-based TWS spatial patterns with multi-decadal-long in situ river level records, to reconstruct past 2-dimensional TWS over a river basin. Results are presented for the Amazon Basin for the period 1980–2008, focusing on the interannual time scale. Results are compared with past TWS estimated by the global hydrological model ISBA-TRIP. Correlations between reconstructed past interannual TWS variability and known climate forcing modes over the region (e.g., El Niño-Southern Oscillation and Pacific Decadal Oscillation) are also estimated. This method offers new perspective for improving our knowledge of past interannual TWS in world river basins where natural climate variability (as opposed to direct anthropogenic forcing) drives TWS variations.

scholarly journals Opportunistically collected photographs can be used to estimate large-scale phenological trends

2019 ◽  
Author(s):  
Shawn D. Taylor ◽  
Robert P. Guralnick
Keyword(s):  
Large Scale ◽  
Sample Sizes ◽  
Multiple Sources ◽  
Model Estimate ◽  
Grid Model ◽  
Spatial Coverage ◽  
Independent Observations ◽  
Historic Data ◽  
Flowering Onset

ABSTRACTPremiseResearch on large-scale patterns of phenology have utilized multiple sources of data to analyze the timing of events such as flowering, fruiting, and leaf out. In-situ observations from standardized surveys are ideal, but remain spatially sparse. Herbarium records and phenology-focused citizen science programs provide a source of historic data and spatial replication, but the sample sizes for any one season are still relatively low. A novel and rapidly growing source of broad-scale phenology data are photographs from the iNaturalist platform, but methods utilizing these data must generalize to a range of different species with varying season lengths and occurring across heterogenous areas. They must also be robust to different sample sizes and potential biases toward well travelled areas such as roads and towns.Methods/ResultsWe developed a spatially explicit model, the Weibull Grid, to estimate flowering onset across large-scales, and utilized a simulation framework to test the approach using different phenology and sampling scenarios. We found that the model is ideal when the underlying phenology is non-linear across space. We then use the Weibull Grid model to estimate flowering onset of two species using iNaturalist photographs, and compare those estimates with independent observations of greenup from the Phenocam network. The Weibull Grid model estimate consistently aligned with Phenocam greenup across four years and broad latitudes.ConclusioniNaturalist observations can considerably increase the amount of phenology observations and also provide needed spatial coverage. We showed here they can accurately describe large-scale trends as long as phenological and sampling processes are considered.

scholarly journals A New Daily Pressure Dataset for Australia and Its Application to the Assessment of Changes in Synoptic Patterns during the Last Century

2010 ◽  
Vol 23 (5) ◽  
pp. 1111-1126 ◽  
Author(s):  
Lisa V. Alexander ◽  
Petteri Uotila ◽  
Neville Nicholls ◽  
Amanda Lynch
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
Past Century ◽  
Strongly Correlated ◽  
Self Organizing Maps ◽  
Sea Level Pressure ◽  
Synoptic Patterns ◽  
The Past

Abstract A high-quality daily dataset of in situ mean sea level pressure was collated for Australia for the period from 1907 to 2006. This dataset was used to assess changes in daily synoptic pressure patterns over Australia in winter using the method of self-organizing maps (SOMs). Twenty patterns derived from the in situ pressure observations were mapped to patterns derived from ERA-40 data to create daily synoptic pressure fields for the past century. Changes in the frequencies of these patterns were analyzed. The patterns that have been decreasing in frequency were generally those most strongly linked to variations in the southern annular mode (SAM) index, while patterns that have increased in frequency were more strongly correlated with variations in the positive phase of El Niño–Southern Oscillation. In general, there has been a reduction in the rain-bearing systems affecting southern Australia since the beginning of the twentieth century. Over the past century, reductions in the frequencies of synoptic patterns with a marked trough to the south of the country were shown to be linked to significant reductions in severe storms in southeast Australia and decreases in rainfall at four major Australian cities: Sydney, Melbourne, Adelaide, and Perth. Of these, Perth showed the most sustained decline in both the mean and extremes of rainfall linked to changes in the large-scale weather systems affecting Australia over the past century. The results suggest a century-long decline in the frequency of low pressure systems reaching southern Australia, consistent with the southward movement of Southern Hemisphere storm tracks. While most of these trends were not significant, associated changes in rainfall and storminess appear to have had significant impacts in the region.

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