Drought indices — Standardized Precipitation Evapotranspiration Index (SPEI) and the self-calibrating Palmer Drought Severity Index (scPDSI) —where derived from 9 United States Historical Climate Network (USHCN) stations on the Chihuahuan Desert in North America for this dataset. USHCN is a subset of the NOAA Cooperative Observer Program (COOP) Network, which consists of selected sites based on spatial coverages and completeness of data. Monthly precipitation depths, minimum, maximum and mean temperature were pulled from the dataset. These drought indices were derived using the SPEI package and scPDSI packages in R. Potential evapotranspiration was also calculated in R using the Thornthwaite method. All 9 sites are within the bounds of the Chihuahuan Desert in the state of New Mexico, with a single site (EL PASO) in the state of Texas.
more »
« less
Constructing a long-term monthly climate data set in central Asia: CONSTRUCTING A LONG-TERM MONTHLY CLIMATE DATA SET IN CENTRAL ASIA
- NSF-PAR ID:
- 10041007
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- International Journal of Climatology
- Volume:
- 38
- Issue:
- 3
- ISSN:
- 0899-8418
- Page Range / eLocation ID:
- 1463 to 1475
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
more » « less
Abstract The temporal variability of precipitation and potential evapotranspiration affects streamflow from daily to long‐term scales, but the relative roles of different climate variabilities on streamflow at daily, monthly, annual, and mean annual scales have not been systematically investigated in the literature. This paper developed a new daily water balance model, which provides a unified framework for water balance across timescales. The daily water balance model is driven by four climate forcing scenarios (observed daily climate and observed daily climate with its intra‐monthly, intra‐annual, and inter‐annual variability removed) and applied to 78 catchments. Daily streamflow from the water balance model is aggregated to coarser timescales. The relative roles of intra‐monthly, intra‐annual, and inter‐annual climate variability are evaluated by comparing the modeled streamflow forced with the climate forcings at two consecutive timescales. It is found that daily, monthly, and annual streamflow is primarily controlled by the climate variability at the same timescale. Intra‐monthly climate variability plays a small role in monthly and annual streamflow variability. Intra‐annual climate variability has significant effects on streamflow at all the timescales, and the relative roles of inter‐annual climate variability are also significant to the monthly and mean annual streamflow, which is often disregarded. The quantitative evaluation of the roles of climate variability reveals how climate controls streamflow across timescales.
-
Abstract Climate change and other anthropogenic stressors have led to long-term changes in the thermal structure, including surface temperatures, deepwater temperatures, and vertical thermal gradients, in many lakes around the world. Though many studies highlight warming of surface water temperatures in lakes worldwide, less is known about long-term trends in full vertical thermal structure and deepwater temperatures, which have been changing less consistently in both direction and magnitude. Here, we present a globally-expansive data set of summertime in-situ vertical temperature profiles from 153 lakes, with one time series beginning as early as 1894. We also compiled lake geographic, morphometric, and water quality variables that can influence vertical thermal structure through a variety of potential mechanisms in these lakes. These long-term time series of vertical temperature profiles and corresponding lake characteristics serve as valuable data to help understand changes and drivers of lake thermal structure in a time of rapid global and ecological change.more » « less
-
more » « less
Abstract Land surface processes are vital to the performance of regional climate models in dynamic downscaling application. In this study, we investigate the sensitivity of the simulation by using the weather research and forecasting (WRF) model at 10-km resolution to the land surface schemes over Central Asia. The WRF model was run for 19 summers from 2000 to 2018 configured with four different land surface schemes including CLM4, Noah-MP, Pleim-Xiu and SSiB, hereafter referred as Exp-CLM4, Exp-Noah-MP, Exp-PX and Exp-SSiB respectively. The initial and boundary conditions for the WRF model simulations were provided by the National Centers for Environmental Prediction Final (NCEP-FNL) Operational Global Analysis data. The ERA-Interim reanalysis (ERAI), the GHCN-CAMS and the CRU gridded data were used to comprehensively evaluate the WRF simulations. Compared with the reanalysis and observational data, the WRF model can reasonably reproduce the spatial patterns of summer mean 2-m temperature, precipitation, and large- scale atmospheric circulation. The simulations, however, are sensitive to the option of land surface scheme. The performance of Exp-CLM4 and Exp-SSiB are better than that of Exp-Noah-MP and Exp-PX assessed by Multivariable Integrated Evaluation (MVIE) method. To comprehensively understand the dynamic and physical mechanisms for the WRF model’s sensitivity to land surface schemes, the differences in the surface energy balance between Ave-CLM4-SSiB (the ensemble average of Exp-CLM4 and Exp-SSiB) and Ave-NoanMP-PX (the ensemble average of Exp-Noah-MP and Exp-PX) are analyzed in detail. The results demonstrate that the sensible and latent heat fluxes are respectively lower by 30.42 W·m−2and higher by 14.86 W·m−2in Ave-CLM4-SSiB than that in Ave-NoahMP-PX. As a result, large differences in geopotential height occur over the simulation domain. The simulated wind fields are subsequently influenced by the geostrophic adjustment process, thus the simulations of 2-m temperature, surface skin temperature and precipitation are respectively lower by about 2.08 ℃, 2.23 ℃ and 18.56 mm·month−1in Ave-CLM4-SSiB than that in Ave-NoahMP-PX over Central Asia continent.
