Chronological Development of Terrestrial Mean Precipitation

2017 ◽  
Vol 98 (11) ◽  
pp. 2411-2428 ◽  
Author(s):  
Kylie J. Park ◽  
Kei Yoshimura ◽  
Hyungjun Kim ◽  
Taikan Oki
Keyword(s):  
Data Exchange ◽  
Research Unit ◽  
Global Scale ◽  
Climatic Research Unit ◽  
Telecommunication System ◽  
Spatial Coverage ◽  
Global Telecommunication System ◽  
The World ◽  
In Situ Observations

Abstract Over 150 years of investigations into global terrestrial precipitation are revisited to reveal how researchers estimated annual means from in situ observations before the age of digitization. After introducing early regional efforts to measure precipitation, the pioneering estimates of terrestrial mean precipitation from the late nineteenth and early twentieth centuries are compared to successive estimates, including those using the latest gridded precipitation datasets available. The investigation reveals that the range of the early estimates is comparable to the interannual variation in terrestrial mean precipitation derived from the latest Climatic Research Unit (CRU) dataset. In-depth revisions of the estimates were infrequent up to the 1970s, due in part to difficulty obtaining and maintaining up-to-date datasets with global coverage. This point is illustrated in a “family tree” that identifies the key publications that subsequent authors referenced, sometimes decades after the original publication. Significant efforts to collate global observations facilitated new investigations and improved data exchange, for example, in the International Hydrological Decade (1965–74) and following the establishment of the Global Telecommunication System under the World Weather Watch Programme of the World Meteorological Organization. Also in the 1970s were the first attempts to adjust in situ observations on a global scale to account for gauge undercatch, and this had a noticeable impact on mean annual estimates. There remains no single satisfactory approach to gauge bias adjustment. Echoing the repeated message of past researchers, today’s authors cite poor spatial coverage, temporal inhomogeneity, and inadequate sharing of in situ observations as the key obstacles to obtaining more accurate estimates of terrestrial mean precipitation.

New record of Munidopsis taiwanica (Decapoda, Anomura) from a mud volcano field in the Mariana Trench, with in-situ observations on habitat

Crustaceana ◽  
2018 ◽  
Vol 91 (3) ◽  
pp. 363-373 ◽  
Author(s):  
Dong Dong ◽  
Xinzheng Li
Keyword(s):  
New Record ◽  
Mud Volcano ◽  
In Situ Observation ◽  
Mariana Trench ◽  
Squat Lobster ◽  
The World ◽  
In Situ Observations ◽  
Seafloor Sediments ◽  
Squat Lobsters

Squat lobsters are prevalent in chemosynthetic environments but have been insufficiently studied in mud volcano habitats. An abyssal species,Munidopsis taiwanicaOsawa, Lin & Chan, 2008 was recently collected in a mud volcano field in the Mariana Trench at a depth greater than 5000 m, which represents a new distributional record. Its diagnostic characters are presented in this study. In-situ observation suggested thatM. taiwanicawas closely associated with this chemosynthetic environment and probably exhibited camouflage behaviour by attaching seafloor sediments onto its body.Munidopsis taiwanicais the first confirmed species of squat lobster found in the mud volcano environment, and currently represents the deepest record (5491 m) of squat lobsters in the world.

scholarly journals Application of machine learning techniques for regional bias correction of snow water equivalent estimates in Ontario, Canada

2020 ◽  
Vol 24 (10) ◽  
pp. 4887-4902
Author(s):  
Fraser King ◽  
Andre R. Erler ◽  
Steven K. Frey ◽  
Christopher G. Fletcher
Keyword(s):  
Machine Learning ◽  
Linear Regression ◽  
Water Resource Management ◽  
Snow Water Equivalent ◽  
Bias Reduction ◽  
Machine Learning Techniques ◽  
Spatial Coverage ◽  
Snow Water ◽  
In Situ Observations

Abstract. Snow is a critical contributor to Ontario's water-energy budget, with impacts on water resource management and flood forecasting. Snow water equivalent (SWE) describes the amount of water stored in a snowpack and is important in deriving estimates of snowmelt. However, only a limited number of sparsely distributed snow survey sites (n=383) exist throughout Ontario. The SNOw Data Assimilation System (SNODAS) is a daily, 1 km gridded SWE product that provides uniform spatial coverage across this region; however, we show here that SWE estimates from SNODAS display a strong positive mean bias of 50 % (16 mm SWE) when compared to in situ observations from 2011 to 2018. This study evaluates multiple statistical techniques of varying complexity, including simple subtraction, linear regression and machine learning methods to bias-correct SNODAS SWE estimates using absolute mean bias and RMSE as evaluation criteria. Results show that the random forest (RF) algorithm is most effective at reducing bias in SNODAS SWE, with an absolute mean bias of 0.2 mm and RMSE of 3.64 mm when compared with in situ observations. Other methods, such as mean bias subtraction and linear regression, are somewhat effective at bias reduction; however, only the RF method captures the nonlinearity in the bias and its interannual variability. Applying the RF model to the full spatio-temporal domain shows that the SWE bias is largest before 2015, during the spring melt period, north of 44.5∘ N and east (downwind) of the Great Lakes. As an independent validation, we also compare estimated snowmelt volumes with observed hydrographs and demonstrate that uncorrected SNODAS SWE is associated with unrealistically large volumes at the time of the spring freshet, while bias-corrected SWE values are highly consistent with observed discharge volumes.

scholarly journals Comparative study on long term climate data sources over South Korea

2018 ◽  
Vol 10 (3) ◽  
pp. 504-523 ◽  
Author(s):  
Dong-Ik Kim ◽  
Dawei Han
Keyword(s):  
South Korea ◽  
Climate Impact ◽  
Climate Data ◽  
The World ◽  
In Situ Observations ◽  
The Mean ◽  
Global Datasets ◽  
Different Parts

Abstract Long term climate data are vitally important in reliably assessing water resources and water related hazards, but in-situ observations are generally sparse in space and limited in time. Although there are several global datasets available as substitutes, there is a lack of comparative studies about their suitability in different parts of the world. In this study, to find out the reliable century-long climate dataset in South Korea, we first evaluate multi-decadal reanalyses (ERA-20 cm, ERA-20c, ERA-40 and NOAA 20th century reanalysis (20CR)) and gridded observations (CRUv3.23 and GPCCv7) for monthly mean precipitation and temperature. In the temporal and statistical comparisons, CRUv3.23 and GPCCv7 for precipitation and ERA-40 for temperature perform the best, and ERA-20c and 20CR also indicate meaningful agreements. For ERA-20 cm, it has only a statistical agreement, but the mean has the difficulty in representing its ensemble. This paper also shows that the applicability of each dataset may vary by region and all products should be locally adjusted before being applied in climate impact assessments. These findings not only help to fill in the knowledge gaps about these datasets in South Korea but also provide a useful guideline for the applicability of the global datasets in different parts of the world.

scholarly journals The 1-way on-line coupled model system MECO(n) – Part 4: Chemical evaluation (based on MESSy v2.52)

2016 ◽  
Author(s):  
Mariano Mertens ◽  
Astrid Kerkweg ◽  
Patrick Jöckel ◽  
Holger Tost ◽  
Christiane Hofmann
Keyword(s):  
Atmospheric Chemistry ◽  
Coupled Model ◽  
Ground Level ◽  
Global Scale ◽  
Model System ◽  
Scale Down ◽  
On Line ◽  
In Situ Observations ◽  
Line Coupling

Abstract. For the first time a simulation incorporating tropospheric and stratospheric chemistry using the newly developed MECO(n) model system is performed. MECO(n) is short for MESSyfied ECHAM and COSMO model nested n-times. It features an on-line coupling of the COSMO-CLM model, equipped with the Modular Earth Submodel System (MESSy) interface (called COSMO/MESSy), with the global atmospheric chemistry model ECHAM5/MESSy for Atmospheric Chemistry (EMAC). This on-line coupling allows a consistent model chain with respect to chemical and meteorological boundary conditions from the global scale down to the regional kilometre scale. A MECO(2) simulation incorporating one regional instance over Europe with 50 km resolution and a one instance over Germany with 12 km resolution is conducted for the evaluation of MECO(n) with respect to tropospheric gas-phase chemistry. The main goal of this evaluation is to ensure, that the chemistry related MESSy submodels and the on-line coupling with respect to the chemistry are correctly implemented. This evaluation is a prerequisite for the further usage of MECO(n) in atmospheric chemistry related studies. Results of EMAC and the two COSMO/MESSy instances are compared with satellite-, ground-based- and aircraft in situ observations, focusing on ozone, carbon monoxide and nitrogen dioxide. Further the methane lifetimes in EMAC and the two COSMO/MESSy instances are analysed in view of the tropospheric oxidation capacity. From this evaluation we conclude that the chemistry related submodels and the on-line coupling with respect to the chemistry are correctly implemented. In comparison with observations both, EMAC and COSMO/MESSy, show strengths and weaknesses. Especially in comparison to aircraft in situ observations COSMO/MESSy shows very promising results. However, the amplitude of the diurnal cycle of ground-level ozone measurements is underestimated. Most of the differences between COSMO/MESSy and EMAC can be attributed to differences in the dynamics of both models, which is subject to further model developments.

Evolution of the Raikoke volcanic plume in the Northern Hemisphere UT/LS over 9 months past eruption as seen from IAGOS-CARIBIC in-situ observations

2021 ◽  
Author(s):  
Andreas Petzold ◽  
Ulrich Bundke ◽  
Marcel Berg ◽  
Rita Gomes ◽  
Jim Haywood ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Research Programme ◽  
Global Scale ◽  
Number Concentration ◽  
Atmospheric Composition ◽  
Volcanic Plume ◽  
Joint Research ◽  
In Situ Observations ◽  
The Impact

<p>IAGOS (In-Service Aircraft for a Global Observing System; www.iagos.org) is a European Research Infrastructure which uses passenger aircraft equipped with autonomous instrumentation for the continuous and global-scale observation of atmospheric composition in the upper troposphere and lowermost stratosphere (UT/LS; see Petzold et al., 2015). Among others, IAGOS provides today detailed information on atmospheric trace species by the flying laboratory in IAGOS-CARIBIC. Since July 2018, number concentration and fraction of non-volatile particles for d<sub>p</sub> > 15 nm as well as size distributions for d<sub>p</sub> >  250 nm are measured (Bundke et al., 2015). Since lately, aerosol chemical composition is provided as well (Schulz et al., 2020). IAGOS-CARIBIC flight routes covered during the period from July 2018 to March 2020 include regular flights from Munich, Germany, to North America, East Asia and South Africa.</p><p>On 22 June 2019, the Raikoke Volcano on the Kuril Islands erupted and transported vast amounts of gaseous and particulate matter into the UT/LS. Two months after the eruption CALIPSO observed enhanced aerosol optical depth and aerosol scattering across the entire lower stratosphere. IAGOS-CARIBIC conducted several flight series in the Northern Hemisphere before and after the eruption phase such that the pre- and post-eruption data provide profound information on the impact of the Raikoke eruption on the Northern Hemisphere UT/LS aerosol and the evolution of the plume during 9 months of regular observation.</p><p>Data indicate an increase in the number concentration of particles with d<sub>p</sub> > 250 nm by a factor of 10 across the entire sampled altitude range, while the increase of the total aerosol number concentration (d<sub>p</sub><sub> </sub>> 15 nm) is less pronounced but also significant. We present a detailed analysis of the changes in UT/LS aerosol load and properties caused by the Raikoke eruption, including the temporal evolution of the aerosol plume during 9 months past the eruption. In-situ observations are backed-up by CALIPSO products and results from associated volcanic plume modelling studies deploying the UK Earth System Model UKESM1.</p><p>The authors gratefully acknowledge the continuous support of IAGOS by Deutsche Lufthansa. Without their commitment these observations would not have been possible. Parts of this study were funded by the German Ministry for Education and Research (BMBF) under Grant No. 01LK1301A as part of the joint research programme IAGOS Germany.</p><p>Bundke, U., et al. (2015) Tellus B 67, 28339 https://doi.org/10.3402/tellusb.v67.28339.</p><p>Petzold, A., et al. (2015) Tellus B 67, 28452 https://doi.org/10.3402/tellusb.v67.28452.</p><p>Schulz, C., et al. (2020) EAC 2020 Abstract <span>ID 1258</span></p>

Assessment and Intercomparison of NOAA Daily Optimum Interpolation Sea Surface Temperature (DOISST) version 2.1

2021 ◽  
pp. 1-57
Author(s):  
Boyin Huang ◽  
Chunying Liu ◽  
Eric Freeman ◽  
Garrett Graham ◽  
Tom Smith ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Optimum Interpolation ◽  
Climate Assessment ◽  
Spatial Coverage ◽  
In Situ Observations ◽  
Mean Square Difference ◽  
Global Oceans

AbstractNOAA Daily Optimum Interpolation Sea Surface Temperature (DOISST) has recently been updated to v2.1 (January 2016–present). Its accuracy may impact the climate assessment, monitoring and prediction, and environment-related applications. Its performance, together with those of seven other well-known sea surface temperature (SST) products, is assessed by comparison with buoy and Argo observations in the global oceans on daily 0.25°×0.25° resolution from January 2016 to June 2020. These seven SST products are NASA MUR25, GHRSST GMPE, BoM GAMSSA, UKMO OSTIA, NOAA GPB, ESA CCI, and CMC.Our assessments indicate that biases and root-mean-square-difference (RMSDs) in reference to all buoys and all Argo floats are low in DOISST. The bias in reference to the independent 10% of buoy SSTs remains low in DOISST, but the RMSD is slightly higher in DOISST than in OSTIA and CMC. The biases in reference to the independent 10% of Argo observations are low in CMC, DOISST, and GMPE; and RMSDs are low in GMPE and CMC. The biases are similar in GAMSSA, OSTIA, GPB, and CCI whether they are compared against all buoys, all Argo, or the 10% of buoy or 10% of Argo observations, while the RMSDs against Argo observations are slightly smaller than those against buoy observations. These features indicate a good performance of DOISST v2.1 among the eight products, which may benefit from ingesting the Argo observations by expanding global and regional spatial coverage of in situ observations for effective bias correction of satellite data.

In Situ TAC Dashboard, an Advanced Tool for visualizing CMEMS In Situ products

2021 ◽  
Author(s):  
Paz Rotllán-García ◽  
Fernando Manzano ◽  
Maria Sotiropoulou ◽  
Keyword(s):  
Product Family ◽  
Spatial Coverage ◽  
Wide Range ◽  
Report Data ◽  
In Situ Observations ◽  
Rest Api ◽  
Marine Environment Monitoring ◽  
Monitoring Service ◽  
User Friendly

<p>The In Situ Thematic Assembly Center (In Situ TAC) for the Copernicus Marine Environment Monitoring Service (CMEMS) is the only data component in the system, out of a total of fifteen, in charge of delivering quality-checked in situ observations in both near real time (NRT products) and delay mode (REP products) for their use in the characterisation of ocean state and variability, assimilation and/or validation activities carried out by the metocean community. </p><p>These in situ observations are gathered by a wide range of platforms (tide gauges, buoys, vessels, CTDs, profilers, gliders, drifters, HF radars, saildrones etc) and include many different parameters (Temperature, Salinity, Sea Level, Currents, Waves, Oxygen, Chlorophyll, Nutrients, Carbon etc). They are made available through known networks and regional data providers to a set of Production Units (PUs) or dedicated Data Centers (Ifremer, PdE, HCMR, IMR, IO-BAS, BSH, SMHI, UiB, CNR, AZTI) where they are quality-checked and homogenized before delivery in terms of format, quality control conventions and standards.</p><p>Unlike most of the products available in the CMEMS catalog (90%), in situ  data products do not naturally provide a regular temporal and spatial coverage or resolution. Indeed, these in situ observations can be available at fixed locations, or on a trajectory, or in a gridded area, at fixed depths or on profiles and the transmitting equipment can be configured to report data in different time samplings. Such a  complexity has traditionally prevented 82% of the In Situ TAC products from fully taking advantage of  CMEMS centralized improvements  in terms of the visualization of datasets (WMS) and subsetting (Subsetter). </p><p>To overcome  this situation, a first version of the CMEMS In Situ TAC Dashboard was released in 2017. This tool provides a user-friendly interface which enables the discovery, subsetting, sharing and downloading of files containing in-situ observations from In Situ TAC multiparameter NRT products. The tool relies on a set of python scripts which process homogenized metadata on an hourly basis as well as complementary information submitted by Sea Data Net (provider overview). The resulting information is then accessible through  the interface with the aid of a json-server REST API, which allows users to make queries and filter the information according to their interest.</p><p>In 2020, the current release of the CMEMS In Situ Dashboard has been officially approved as an “Advanced Visualization Tool” by CMEMS and is now showcased as a complementary tool to the official viewer. Future developments will explore its extension to the whole In Situ product family (beyond the present In Situ multiparameter NRT datasets), the improvement of data visualization options (currently using EMODnet widget services) and the implementation of data discovery capabilities.</p>

scholarly journals CARIBIC DOAS observations of nitrous acid and formaldehyde in a large convective cloud

2014 ◽  
Vol 14 (13) ◽  
pp. 6621-6642 ◽  
Author(s):  
K.-P. Heue ◽  
H. Riede ◽  
D. Walter ◽  
C. A. M. Brenninkmeijer ◽  
T. Wagner ◽  
...  
Keyword(s):  
Nitrous Acid ◽  
World Wide ◽  
Convective Cloud ◽  
Global Scale ◽  
Box Model ◽  
Convective System ◽  
Mixing Ratios ◽  
The World ◽  
Tropopause Region

Abstract. The chemistry in large thunderstorm clouds is influenced by local lightning-NOx production and uplift of boundary layer air. Under these circumstances trace gases like nitrous acid (HONO) or formaldehyde (HCHO) are expected to be formed or to reach the tropopause region. However, up to now only few observations of HONO at this altitude have been reported. Here we report on a case study where enhancements in HONO, HCHO and nitrogen oxides (NOx) were observed by the CARIBIC flying laboratory (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container). The event took place in a convective system over the Caribbean Sea in August 2011. Inside the cloud the light path reaches up to 100 km. Therefore the DOAS instrument on CARIBIC was very sensitive to the tracers inside the cloud. Based on the enhanced slant column densities of HONO, HCHO and NO2, average mixing ratios of 37, 468 and 210 ppt, respectively, were calculated. These data represent averages for constant mixing ratios inside the cloud. However, a large dependency on the assumed profile is found; for HONO a mixing ratio of 160 ppt is retrieved if the total amount is assumed to be situated in the uppermost 2 km of the cloud. The NO in situ instrument measured peaks up to 5 ppb NO inside the cloud; the background in the cloud was about 1.3 ppb, and hence clearly above the average outside the cloud (≈ 150 ppt). The high variability and the fact that the enhancements were observed over a pristine marine area led to the conclusion that, in all likelihood, the high NO concentrations were caused by lighting. This assumption is supported by the number of flashes that the World Wide Lightning Location Network (WWLLN) counted in this area before and during the overpass. The chemical box model CAABA is used to estimate the NO and HCHO source strengths which are necessary to explain our measurements. For NO a source strength of 10 × 109 molec cm−2 s−1 km−1 is found, which corresponds to the lightning activity as observed by the World Wide Lightning Location network, and lightning emissions of 5 × 1025 NO molec flash−1 (2.3–6.4 × 1025). The uncertainties are determined by a change of the input parameters in the box model, the cloud top height and the flash density. The emission rate per flash is scaled up to a global scale and 1.9 (1.4–2.5) tg N a−1 is estimated. The HCHO updraught is of the order of 120 × 109 molec cm−2 s−1 km−1. Also isoprene and CH3OOH as possible HCHO sources are discussed.

scholarly journals On the Long-Wavelength Validation of the SWOT KaRIn Measurement

2019 ◽  
Vol 36 (5) ◽  
pp. 843-848 ◽  
Author(s):  
Jinbo Wang ◽  
Lee-Lueng Fu
Keyword(s):  
Wavelength Range ◽  
Spatial Scales ◽  
Global Ocean ◽  
Short Wavelength Range ◽  
Long Wavelength ◽  
Spatial Coverage ◽  
In Situ Observations ◽  
Wavenumber Spectrum ◽  
Ocean Topography

AbstractThe Surface Water and Ocean Topography (SWOT) mission will measure the sea surface height (SSH) using a Ka-band radar interferometer (KaRIn) over a swath off the nadir of the satellite tracks. The mission requires calibration and validation (CalVal) of the SSH wavenumber spectrum at wavelengths between 15 and 1000 km. The CalVal in the short-wavelength range (15–150 km) requires in situ observations. In the long-wavelength range (150–1000 km), the CalVal will use the onboard Jason-class nadir altimeter. Using a high-resolution global ocean simulation, this study identifies the spatial scales beyond which the nadir and off-nadir observations can be considered comparable. Our results suggest that the ocean signals at nadir can represent off-nadir ocean signals at wavelengths longer than 120 and 70 km along the midswath and the inner edge of the KaRIn grid, respectively, indicating that the nadir altimeter is able to fulfill its goal to validate the long-wavelength KaRIn measurement. The wavelength along the inner edge is limited around 70 km because the onboard nadir altimeter cannot resolve spatial scales longer than ~70 km. These wavelengths provide a reference point for the required spatial coverage of the SWOT SSH in situ CalVal.

scholarly journals Enhancing Model Skill by Assimilating SMOPS Blended Soil Moisture Product into Noah Land Surface Model

2015 ◽  
Vol 16 (2) ◽  
pp. 917-931 ◽  
Author(s):  
Jifu Yin ◽  
Xiwu Zhan ◽  
Youfei Zheng ◽  
Jicheng Liu ◽  
Li Fang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Surface Model ◽  
Spatial Coverage ◽  
In Situ Observations ◽  
The Impact

Abstract Many studies that have assimilated remotely sensed soil moisture into land surface models have generally focused on retrievals from a single satellite sensor. However, few studies have evaluated the merits of assimilating ensemble products that are merged soil moisture retrievals from several different sensors. In this study, the assimilation of the Soil Moisture Operational Products System (SMOPS) blended soil moisture (SBSM) product, which is a combination of soil moisture products from WindSat, Advanced Scatterometer (ASCAT), and Soil Moisture and Ocean Salinity (SMOS) satellite sensors is examined. Using the ensemble Kalman filter (EnKF), a synthetic experiment is performed on the global domain at 25-km resolution to assess the impact of assimilating the SBSM product. The benefit of assimilating SBSM is assessed by comparing it with in situ observations from U.S. Department of Agriculture Soil Climate Analysis Network (SCAN) and the Surface Radiation Budget Network (SURFRAD). Time-averaged surface-layer soil moisture fields from SBSM have a higher spatial coverage and generally agree with model simulations in the global patterns of wet and dry regions. The impacts of assimilating SMOPS blended data on model soil moisture and soil temperature are evident in both sparsely and densely vegetated areas. Temporal correlations between in situ observations and net shortwave radiation and net longwave radiation are higher with assimilating SMOPS blended product than without the data assimilation.

Sign in / Sign up

Export Citation Format

Share Document