Weather and climate forecasts: Difference between revisions
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Climate forecasts and outlooks are consulted by stakeholders, including agricultural producers and water managers, but because of their relatively low forecasts accuracy/skill it is challenging to use them to support planning and decision-making like how weather forecasts and seasonal streamflow forecasts are used. Reclamation and CBRFC are exploring ways to incorporate climate forecasts into basin runoff and reservoir outlooks. | Climate forecasts and outlooks are consulted by stakeholders, including agricultural producers and water managers, but because of their relatively low forecasts accuracy/skill it is challenging to use them to support planning and decision-making like how weather forecasts and seasonal streamflow forecasts are used. Reclamation and CBRFC are exploring ways to incorporate climate forecasts into basin runoff and reservoir outlooks. | ||
== | ==Weather forecasts== | ||
Because we notice when weather forecasts are wrong, we may not fully appreciate how often they are right, and that they continue to improve. Forecast skill for mid-latitude regions has been increasing by about 1 day per decade; today’s 5-day weather forecast is as skillful as the 4-day forecast was 10 years ago, or the 3-day forecast 20 years ago. | |||
The main source of predictability and skill for weather forecasts is the accurate description of the initial conditions of the atmosphere by global networks of observations from land and ocean stations, satellites, and aircraft. Once initialized with those observations, a weather forecast model simulates the evolution of the large-scale weather patterns. The skill of weather forecasts declines with increasing lead time because the information contained in the initial patterns is gradually lost to unpredictable chaotic motions of the atmosphere. | |||
Weather forecast models are massively complex physics-based simulation models that are run on supercomputers. They have a basic structure, equations, and features akin to Global climate models (GCMs). Like GCMs, most weather models are global in scope, though very-high-resolution regional weather models are also used for short-term forecasts of 48 hours or less. For weather forecasts for the U.S., including the Colorado River Basin, the NOAA National Weather Service relies mainly on the NOAA GFS (Global Forecast System) model, supplemented with the primary European and Canadian global forecast models, and higher-resolution U.S. regional models. Forecasters at the local NWS offices use the forecast model output as ''guidance'', often manually tuning the official forecasts in accordance with their knowledge of local weather and the strengths and weaknesses of the models. | |||
==Subseasonal climate forecasts== | |||
==Seasonal climate forecasts== | |||
==Decadal climate forecasts== | |||
Revision as of 14:49, 25 May 2021
Subseasonal climate forecasts Seasonal climate forecasts Decadal climate forecasts
Overview
Weather and climate forecasts address the ubiquitous desire to know what the weather (temperature, precipitation, winds, cloud cover, etc.) will be like over the coming hours, days, weeks, and months. Weather forecasts refer to forecast periods of 14 days or less, a time frame over which the evolution of the current atmospheric pattern can be more directly predicted, and very specific and high-resolution (in time and space) predictions of weather variables can be made. The skill of weather forecasts over mid-latitude continental areas like the Colorado River Basin is very high for the first 1-2 days, lower for the next 3-4 days, and then drops off dramatically.
Climate forecasts or outlooks are for longer periods (14 days to several months or more), and over these time frames, what is typically forecasted is tendencies towards weather anomalies (warmer/cooler temperatures; higher/lower precipitation) rather than specific quantities. Both the spatial and temporal resolution of the climate forecasts tend to be lower. The sources of predictability for climate forecasts are more diverse than for weather forecasts, which depend mainly on capturing the initial conditions and patterns of the atmosphere. The skill of climate forecasts is much lower than for weather forecasts in all parts of the world, and this is true also in the Colorado River Basin.
Incomplete knowledge about future weather conditions is a major uncertainty in streamflow forecasts; most of the forecast error in April 1st seasonal streamflow forecasts is due to weather over the April-July period being different from that assumed in the most-probable forecast (the average of past April-July temperature and precipitation).
Relevance
Weather forecasts (out to 10 days) are routinely used by stakeholders across the basin for guiding short-term operational decision-making, such as in agriculture, recreation, and transportation, and water resource management. NOAA Colorado Basin River Forecast Center (CBRFC) incorporates weather forecasts (out to 10 days) into their short-term streamflow forecasts and peak runoff forecasts, and also into their Seasonal streamflow forecasts.
Climate forecasts and outlooks are consulted by stakeholders, including agricultural producers and water managers, but because of their relatively low forecasts accuracy/skill it is challenging to use them to support planning and decision-making like how weather forecasts and seasonal streamflow forecasts are used. Reclamation and CBRFC are exploring ways to incorporate climate forecasts into basin runoff and reservoir outlooks.
Weather forecasts
Because we notice when weather forecasts are wrong, we may not fully appreciate how often they are right, and that they continue to improve. Forecast skill for mid-latitude regions has been increasing by about 1 day per decade; today’s 5-day weather forecast is as skillful as the 4-day forecast was 10 years ago, or the 3-day forecast 20 years ago.
The main source of predictability and skill for weather forecasts is the accurate description of the initial conditions of the atmosphere by global networks of observations from land and ocean stations, satellites, and aircraft. Once initialized with those observations, a weather forecast model simulates the evolution of the large-scale weather patterns. The skill of weather forecasts declines with increasing lead time because the information contained in the initial patterns is gradually lost to unpredictable chaotic motions of the atmosphere.
Weather forecast models are massively complex physics-based simulation models that are run on supercomputers. They have a basic structure, equations, and features akin to Global climate models (GCMs). Like GCMs, most weather models are global in scope, though very-high-resolution regional weather models are also used for short-term forecasts of 48 hours or less. For weather forecasts for the U.S., including the Colorado River Basin, the NOAA National Weather Service relies mainly on the NOAA GFS (Global Forecast System) model, supplemented with the primary European and Canadian global forecast models, and higher-resolution U.S. regional models. Forecasters at the local NWS offices use the forecast model output as guidance, often manually tuning the official forecasts in accordance with their knowledge of local weather and the strengths and weaknesses of the models.
Subseasonal climate forecasts
Seasonal climate forecasts
Decadal climate forecasts
Data and Tools
Additional Resources
State of the Science Report
Chapter 8 of the State of the Science report covers many aspects of Streamflow Forecasting in greater detail; Section 8.4 is specific to mid-range forecasts (seasonal and longer). Chapter 6, on Hydrologic Modeling, has a detailed description of the CBRFC forecast model framework in Section 6.3, under National Weather Service Models.
Research Directions
New and Notable Research (2020-present)
Summary